Reading Group
20 January 2006
A. Corduneanu and C.M. Bishop, Variational Bayesian Model Selection for Mixture Distributions
Presenter: Shihao Ji, Presentation
27 January 2006
M. Kuss and C. Rassmussen, Assessing Approximations for Gaussian Process Classification
Presenter: David Williams, Presentation
3 February 2006
A. Niculescu-Mizil and R. Caruana, Learning the Structure of Related Tasks
Presenter: Lihan He, Presentation
17 February 2006
Y.W. The, M.I. Jordan, M.J. Beal and D.M. Blei, Sharing Clusters Among Related Groups: Hierarchical Dirichlet Process
Presenter: Kai Ni, Presentation
24 February 2006
E. Bart and S. Ullman, Cross-Generalization: Learning Novel Classes From A Single Example By Feature Replacement
Presenter: Nilanjan Dasgupta, Presentation
3 March 2006
H. Ishwaran and L.F. James, Gibbs Sampling Methods for Stick-Breaking Priors
Presenter: Yuting Qi, Presentation
10 March 2006
T.L. Griffiths and Z. Ghahramani, Infinite Latent Feature Models and the Indian Buffet Process
Presenter: Ya Xue, Presentation
17 March 2006
E. Meeds and S. Osindero, Bayes Sets
Presenter: Qi An, Presentation
23 March 2006
Y. Wang and Q. Ji, A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences
Presenter: Qiuhua Liu, Presentation
31 March 2006
N. Mehta, S. Natarajan, P. Tadepalli and A. Fern, Transfer in Variable-reward Hierarchical Reinforcement Learning
Presenter: Hui Li, Presentation
7 April 2006
J. Zhang, Z. Ghahramani, Y. Yang, Learning Multiple Related Tasks using Latent Independent Component Analysis
Presenter: Iulian Pruteanu, Presentation
14 April 2006
O.L. Mangasarian and E.W. Wild, Multisurface Proximal SVM Classification via Generalized Eigenvalues
Presenter: Jun Fang, Presentation
21 April 2006
A. Eliazar and R. Parr, DP-SLAM: Fast, Robust Simultaneous Localization and Mapping without Predetermined Landmarks
A. Eliazar and R. Parr, DP-SLAM 2.0
A. Eliazar and R. Parr, Constant/Linear Time Simultaneous Localization and Mapping for Dense Maps
Presenter: Lihan He, Presentation
28 April 2006
D.B. Dunson and N. Pillai, Bayesian Density Regression
Presenter: Ya Xue, Presentation
5 May 2006
R.R. Coifman et al., Geometric Diffusions as a Tool for Harmonic Analysis and Structure Definition of Data: Diffusion Maps
Presenter: Xuejun Liao, Presentation
12 May 2006
R.R. Coifman et al., Geometric Diffusions as a Tool for Harmonic Analysis and Structure Definition of Data: Multiscale Methods
Presenter: Shihao Ji, Presentation
19 May 2006
E. Sudderth, A. Torralba, W. Freeman and A. Willsky, Describing Visual Scenes Using Transformed Dirichlet Processes
Presenter: Kai Ni, Presentation
26 May 2006
S. Mahadevan and M. Maggioni, Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions
Presenter: Qi An, Presentation
2 June 2006
B. Nadler, S. Lafon, R. Coifman, I. Kevrekidis, Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators
Presenter: Nilanjan Dasgupta, Presentation
19 June 2006
M. Szummer and T. Jaakkola, Partially Labeled Classification with Markov Random Walks
Presenter: Xuejun Liao, Presentation
7 July 2006
B. Wolfe, M.R. James and S. Singh, Learning Predictive State Representations
Presenter: Hui Li, Presentation
14 July 2006
D. Justice and A. Hero, A Binary Linear Programming Formulation of the Graph Edit Distance
Presenter: Shihao Ji, Presentation
21 July 2006
X.L. Nguyen, M.J. Wainwright, M.I. Jordan, On Optimal Quantization Rules for Sequential Decision Problems
Presenter: Qi An, Presentation
28 July 2006
L. Fei-Fei and P. Perona, A Bayesian Hierarchical Model for Learning Natural Scene Categories
D. Blei and J.D. Lafferty, Dynamic Topic Models
Presenter: Iulian Pruteanu, Presentation
4 August 2006
D. Blei, J. Lafferty, Correlated Topic Models
Presenter: Chunping Wang, Presentation
25 August 2006
E.P. Xing, K.-A. Sohn, M.I. Jordan and Y.-W. Teh, Bayesian Multi-Population Haplotype Inference via a Hierarchical Dirichlet Process Mixture
Presenter: Kai Ni, Presentation
4 September 2006
D. Hähnel, D. Fox, W. Burgard, and S. Thrun, A highly efficient FastSLAM algorithm for generating cyclic maps of large-scale environments from raw laser range measurements
G. Grisetti, C. Stachniss, and W. Burgard, Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling
Presenter: Lihan He, Presentation
11 September 2006
J. Langford and B. Zadrozny, Reducing T-step Reinforcement Learning to Classification
D. Blatt and A. O. Hero, From weighted classification to policy search
Presenter: Hui Li, Presentation
22 September 2006
A. Hyvarinen and P. Hoyer, Emergence of Phase- and Shift-Invariant Features by decomposition of Natural Images into Independent feature Subspaces
A. Hyvarinen, P.O. Hoyer and M. Inki, Topographic Independent Component Analysis
Presenter: Iulian Pruteanu, Presentation
29 September 2006
S. Lafton and A.B. Lee, Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameterization
Presenter: Shihao Ji, Presentation
6 October 2006
O. Papaspiliopoulos and G.O. Roberts, Retrospective MCMC Methods for DP Hierarchical Models
Presenter: Yuting Qi, Presentation
13 October 2006
O. Papaspiliopoulos and G.O. Roberts, Retrospective MCMC Methods for DP Hierarchical Models and comparison of MCMC samplers for Dirichlet processors
Presenter: Yuting Qi, Presentation
20 October 2006
Graphical techniques for semi-supervised learning
Presenter: Xuejun Liao, Presentation
27 October 2006
F. Wood, T.L. Griffiths and Z. Ghahramani, A Non-Parametric Bayesian Method of Inferring Hidden Causes
Presenter: Qi An, Presentation
3 November 2006
S. Lafton, Y. Keller and R.R. Coiffman, Data Fusion and Multi-Cue Data Matching by Diffusion Maps
Presenter: Chunping Wang, Presentation
10 November 2006
A. Rodriguez, D.B. Dunson and A.E. Gelfand, The Nested Dirichlet Process
Presenter: Kai Ni, Presentation
17 November 2006
A.E. Raftery and S. Lewis, How Many Iterations in the Gibbs Sampler
Presenter: Iulian Pruteanu, Presentation
5 December 2006
M.K. Cowles and B.P. Carlin, MCMC Convergence Diagnostics: A Comparative Review
Presenter: Yuting Qi, Presentation
12 January 2007
T. Smith and R. Simmons, Heuristic Search Value Iteration for POMDPs
Presenter: Hui Li, Presentation
19 January 2007
D.B. Dunson and J.-H. Park, Kernel Stick-Breaking Processes
Presenter: Qi An, Presentation
26 January 2007
D.B. Dunson, Bayesian Dynamic Modeling of Latent Trait Distributions
Presenter: Kai Ni, Presentation
2 February 2007
N. Tatti, Distances Between Data Sets Based on Summary Statistics
Presenter: Yuting Qi, Presentation
9 February 2007
E.J. Candes, J. Romberg, T. Tao, Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information
E. Candes and J. Romberg, Practical Signal Recovery from Random Projections
Presenter: Dehong Liu, Presentation
16 February 2007
S. Kim and P. Smyth, Segmental Hidden Markov Models with Random Effects for Waveform Modeling
Presenter: Lu Ren, Presentation
23 February 2007
E.P. Xing and K.-A. Sohn, A New Nonparametric Bayesian Model for Genetic Recombination in Open Ancestral Space
Presenter: Chunping Wang, Presentation
9 March 2007
K. Watanabe and Sumio Watanabe, Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation
Presenter: Iulian Pruteanu, Presentation
16 March 2007
T. De Bie and N. Cristianini, Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problems
Presenter: Lihan He, Presentation
23 March 2007
D. Zhou, O. Bousquet, T. Navin Lal, J. Weston and B. Scholkopf, Learning with Local and Global Consistency
Presenter: Qiuhua Liu, Presentation
30 March 2007
P. K. Shivaswamy, C. Bhattacharyya and A.J. Smola, Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
Presenter: Qi An, Presentation
6 April 2007
H. Raghavan, O. Madani and R. Jones, Active Learning with Feedback on Both Features and Instances
Presenter: John Paisley, Presentation
27 April 2007
F. Dominici, G. Parmigiani, K.H. Reckhow and R.L. Wolpert, Combining Information from Related Regressions
Presenter: Kai Ni, Presentation
4 May 2007
F.R. Bach and M.I. Jordan, Learning Spectral Clustering, With Application to Speech Processing
Presenter: Yuting Qi, Presentation
11 May 2007
E. Evan-Dar, S. Mannor and Y. Mansour, Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems
Presenter: Shihao Ji, Presentation
18 May 2007
F.R. Bach, D. Heckerman, E. Horvitz, Considering Cost Asymmetry in Learning Classifiers
Presenter: Chunping Wang, Presentation
30 May 2007
R. Munos, Policy Gradient in Continuous Time
Presenter: Hui Li, Presentation
8 June 2007
D. Tao1, X. Li, X. Wu and S.J. Maybank, General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
Presenter: Iulian Pruteanu, Presentation
15 June 2007
R. Thibaux and M.I. Jordan, Hierarchical Beta Processes and the Indian Buffet Process
Presenter: Qi An, Presentation
9 July 2007
T. Liu, A.W. Moore and A. Gray, New Algorithms for Efficient High-Dimensional Nonparametric Classification
Presenter: Yuting Qi, Presentation
18 July 2007
S. Whiteson and P. Stone, Evolutionary Function Approximation for Reinforcement Learning
Presenter: Xuejun Liao, Presentation
27 July 2007
Y.W. Teh, D. Gorur, Z. Ghahramani, Stick-breaking construction for the Indian buffet process
Presenter: Kai Ni, Presentation
6 August 2007
A.D. Szlam, M. Maggioni and R.R. Coifman, Regularization on Graphs with Function-Adapted Diffusion Process
Presenter: Eric Wang, Presentation
15 August 2007
H. Ishwaran and M. Zarepour, Dirichlet Prior Sieves in Finite Normal Mixtures
Presenter: John Paisley, Presentation
31 August 2007
K. Kurihara, M. Welling and Y.W. Teh, Collapsed Variational Dirichlet Process Mixture Models
Presenter: Qi An, Presentation
7 September 2007
J. Hoey and J.J. Little, A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation
Presenter: Iulian Pruteanu, Presentation
14 September 2007
S. Yu, V. Tresp and K. Yu, Robust Multi-Task Learning with t-Processes
Presenter: Ivo Shterev, Presentation
21 September 2007
P. Quelhas, F. Monay, J.M. Odobez, D. Gatica-Perez and T. Tuytelaars, A Thousand Words in a Scene
Presenter: Yuting Qi, Presentation
5 October 2007
P. Domingos and M. Pazzani, On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Presenter: Lu Ren, Presentation
18 October 2007
Q. Wu, J. Guinney, M. Maggioni and S. Mukherjee, Learning Gradients: Predictive Models that Infer Geometry and Dependence
Presenter: Xuejun Liao, Presentation
26 October 2007
R.M. Neal, Density Modeling and Clustering Using Dirichlet Diffusion Trees
Presenter: Ivo Shterev, Presentation
2 November 2007
J. Guinney, Q. Wu and S. Mukherjee, Estimating Variable Structure and Dependence in Multi-Task Learning via Gradients
Presenter: John Paisley, Presentation
16 November 2007
M. Belkin and P. Niyogi, Using Manifold Structure for Partially Labelled Classification
Presenter: Chunping Wang, Presentation
30 November 2007
R. Castelo and A. Roverato, A Robust Procedure For Gaussian Graphical Model Search From Microarray DataWith p Larger Than n
Presenter: Kuan-Ming Lin, Presentation
7 December 2007
Y.W. The, K. Kurihara and M. Welling, Collapsed Variational Inference for HDP
Presenter: Iulian Pruteanu, Presentation
18 January 2007
H. Ishwaran and M. Zarepour, Exact and Approximate Sum Representations for the Dirichlet Process
Presenter: John Paisley, Presentation
25 January 2007
A.B. Owen, Infinitely Imbalanced Logistic Regression
Presenter: Ivo Shterev, Presentation
15 February 2008
J.-H. Park and D. Dunson, Bayesian Generalized Product Partition Model
Presenter: Eric Wang, Presentation
22 February 2008
R.F. MacLehose and D.B. Dunson, Bayesian semi-parametric multiple shrinkage
Presenter: Lu Ren, Presentation
3 March 2008
W. Li, D. Blei and A. McCallum, Nonparametric Bayes Pachinko Allocation
Presenter: Lihan He, Presentation
12 March 2008
N. Bouguila and D. Ziou, High-Dimensional Unsupervised Selection & Estimation of a Finite Generalized Dirichlet Mixture Model Based on MML
Presenter: Qi An, Presentation
21 March 2008
S. Ray and B. Mallik, Functional Clustering by Bayesian Wavelet Methods
Presenter: Iulian Pruteanu, Presentation
4 April 2008
M. West, Bayesian Factor Regression Models in the “Large p, Small n” Paradigm
Presenter: John Paisley, Presentation
11 April 2008
M. Dundar, B. Krishnapuram, J. Bi and R. Rao, Learning Classifiers When the Training Data Are Not IID
Presenter: Ivo Shterev, Presentation
18 April 2008
Y. Sun, M. Kamel and Y. Wang, Boosting for Learning Multiple Classes with Imbalanced Class Distribution
Presenter: Minhua Chen, Presentation
25 April 2008
H.M. Wallach, Topic Modeling: Beyond Bag of Words
Presenter: Eric Wang, Presentation
2 May 2008
J. Baxter, A Model of Inductive Bias Learning
S. Ben David and R.S. Borbely, A Notion of Task Relatedness Yielding Provable Multiple-task Learning Guarantees
Presenter: Xuejun Liao, Presentation
9 May 2008
J. Canny and T. Rattenbury, A Dynamic Topic Model for Document Segmentation
Presenter: Lan Du, Presentation
16 May 2008
S.M. O’Brien and D. Dunson, Bayesian Multivariate Logistic Regression
Presenter: Lihan He, Presentation
23 May 2008
M.Y. Park and T. Hastie, Penalized Logistic Regression for Detecting Gene Interactions
Presenter: Minhua Chen, Presentation
30 May 2008
J. Amores, N. Sebe and P. Radeva, Context-Based Object-Class Recognition and Retrieval by Generalized Correlograms
Presenter: Qi An, Presentation
6 June 2008
D.M Blei and J.D. McAuliffe, Supervised Topic Models
Presenter: Iulian Pruteanu, Presentation
13 June 2008
S. Gould, J. Rodgers, D. Cohen, G. Elidan, D. Koller, Multi-Class Segmentation with Relative Location Prior
Presenter: Lan Du, Presentation
20 June 2008
C. Wang, D. Blei and D. Heckerman, Continuous Time Dynamic Topic Models
Presenter: Ivo Shterev, Presentation
27 June 2008
P. Liang and M.I. Jordan, An Asymptotic Analysis of Generative, Discriminative and Pseudolikelihood Estimators
Presenter: Lihan He, Presentation
3 July 2008
G. Chechik, G. Heitz, G. Elidan, P. Abbeel, D. Koller, Max-margin Classification of Data with Absent Features
Presenter: Chunping Wang, Presentation
11 July 2008
E.B. Fox, E.B. Sudderth, M.I. Jordan and A.S. Willsky, An HDP-HMM for Systems with State Persistence
Presenter: Lu Ren, Presentation
18 July 2008
M.B. Wakin and R.G. Baraniuk, Random projections of signal manifolds
C. Hegde, M.B. Wakin and R.G. Baraniuk, Random projections for manifold learning
R.G. Baraniuk and M.B. Wakin, Random projections of smooth manifolds
Presenter: John Paisley, Presentation
25 July 2008
S.J.D. Prince and J.H. Elder, Tied factor analysis for face recognition across large pose changes
Presenter: Lan Du, Presentation
1 August 2008
G. Elidan, B. Packer, G. Heitz and D. Koller, Convex Point Estimation using Undirected Bayesian Transfer Hierarchies
Presenter: Haojun Chen, Presentation
8 August 2008
P. Liang, D. Klein and M.I. Jordan, Agreement-Based Learning
Presenter: Xuejun Liao, Presentation
22 August 2008
M. Girolami and S. Rogers, Variational Bayesian multinomial probit regression with Gaussian priors
Presenter: Minhua Chen, Presentation
29 August 2008
X.Z. Fern and C.E. Brodley, Random Projection for High Dimensional Data Clustering: A Cluster Ensemble Approach
Presenter: Dehong Liu, Presentation
5 September 2008
K.T. Miller, T.L. Griffiths and M.I. Jordan, The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features
Presenter: John Paisley, Presentation
12 September 2008
T.L. Griffiths, M. Steyvers, D.M. Blei and J.B. Tenenbaum, Integrating Topics and Syntax
Preseneter: Eric Wang, Presentation
19 September 2008
L. Meier, S. van de Geer and P. Buhlmann, The Group Lasso for Logistic Regression
Presenter: Lu Ren, Presentation
3 October 2008
P. Poupart and N. Vlassis, Model-based Bayesian Reinforcement Learning in Partially Observable Domains
Presenter: Lihan He, Presentation
17 October 2008
P. Indyk and R. Motwani, Approximate Nearest Neighbors: Towards Removing the Curse of Dimensionality
Presenter: Dehong Liu, Presentation
24 October 2008
J.A. Duan, M. Guindani and A.E. Gelfand, Generalized Spatial Dirichlet Process Models
Presenter: Lu Ren, Presentation
31 October 2008
R. Tibshirani, Regression Shrinkage and Selection via the Lasso
A.E. Hoerl and R.W. Kennard, Ridge Regression: Biased Estimation for Nonorthogonal Problems
Presenter: John Paisley, Presentation
7 November 2008
H. Zou and T. Hastie, Regularization and Variable Selection via the Elastic Net
Presenter: Minhua Chen, Presentation
14 November 2008
J. van Gael, Y. Saatci, Y.W. Teh and Z. Ghahramani, Beam Sampling for the Infinite HMM
Presenter: Lihan He, Presentation
28 November 2009
Y. Gal and A. Pfeffer, Networks of Influence Diagrams: A Formalism for Representing Agents’ Beliefs and Decision Making
Presenter: Chenghui Cai, Presentation
17 December 2008
S. Shringarpure and E.P. Xing, mStruct: A New Admixture Model for Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations
Presenter: Haojun Chen, Presentation
5 January 2009
R. Gomes, M. Welling and P. Perona, Memory Bounded Inference in Topic Models
Presenter: Eric Wang, Presentation
14 January 2009
P. Orbanz and J.M. Buhmann, Smooth Image Segmentation by Nonparametric Bayesian Inference
Presenter: Lan Du, Presentation
30 January 2008
D. Achlioptas, Database Friendly Random Projections
Presenter: Xuejun Liao, Presentation
6 February 2009
M.A.T. Figueiredo, D.S. Cheng and V. Murino, Clustering Under Prior Knowledge with Application to Image Segmentation
Presenter: Lu Ren, Presentation
23 February 2009
G. Sfikas, C. Nikou and N. Galatsanos, Edge Preserving Spatially Varying Mixtures for Image Segmentation
Presenter: Lihan He, Presentation
2 March 2009
A. Gruber, M. Rosen-Zvi and Y. Weiss, Hidden Topic Markov Models
Presenter: Chunping Wang, Presentation
13 March 2009
Y. Qi and T.S. Jaakkola, Parameter Expanded Variational Bayesian Methods
Presenter: John Paisley, Presentation
20 March 2009
H.D. Bondell and B.J. Reich, Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR
Presenter: Minhua Chen, Presentation
27 March 2009
P. Rai and H. Daume III, The Infinite Hierarchical Factor Regression Model
Presenter: Bo Chen, Presentation
3 April 2009
J.B. Tenenbaum, V. de Silva and J.C. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction
Presenter: Mingyuan Zhou, Presentation
10 April 2009
A. Krause and C. Guestrin, Near-Optimal Observation Selection Using Submodular Functions
Presenter: Haojun Chen, Presentation
17 April 2009
J. Haupt, R. Castro and R. Nowak, Distilled Sensing: Selective Sampling for Sparse Signal Recovery
Presenter: Lihan He, Presentation
24 April 2009
X. Wang, X. Ma and E. Grimson, Unsupervised Activity Perception by Hierarchical Bayesian Models
Presenter: Xuejun Liao, Presentation
8 May 2009
L.-J. Li, R. Socher and L. Fei-Fei, Towards Total Scene Understanding: Automatic Classification, Annotation and Segmentation
Presenter: Eric Wang, Presentation
22 May 2009
X. Nguyen and A.E. Gelfand, The Dirichlet Labeling Process for Functional Data Analysis
Presenter: Lu Ren, Presentation
1 June 2009
T. Shi, M. Belkin, B. Yu, Data Spectroscopy: Learning Mixture Models using Eigenspaces of Convolution Operators
Presenter: Jorge Silva, Presentation
12 June 2009
A.M. Bruckstein, D.L. Donoho and M. Elad, From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals & Images
Presenter: Mingyuan Zhou , Presentation
19 June 2009
J.M. Duarte-Carvajalino and G. Sapiro, Learning to Sense Sparse Signals
Presenter: Haojun Chen , Presentation
26 June 2009
J. Sivic and A. Zisserman, Efficient Visual Search of Videos Case as Text Retrieval
Presenter: John Paisley, Presentation
3 July 2009
C. Wang, D. Blei and L. Fei-Fei, Simultaneous Image Classification and Annotation
Presenter: Eric Wang, Presentation
10 July 2009
Presenter: Chunping Wang, Presentation
17 July 2009
D.B. Dunson, Multivariate Kernel Partition Processes
Presenter: Lan Du, Presentation
24 July 2009
M. Elad and I. Yavneh, A Weighted Average of Sparse Representations is Better than the Sparsest One Alone
Presenter: Dehong Liu, Presentation
31 July 2009
R.P. Adams, I. Murray and D.J.C. MacKay, Tractable Nonparametric Bayesian Inference in Poisson Processes with Gaussian Process Intensities
Presenter: Lihan He, Presentation
14 August 2009
T. Tieleman and G. Hinton, Using Fast Weights to Improve Persistent Contrastive Divergence
Presenter: Jorge Silva, Presentation
21 August 2009
R.P. Adams and Z. Ghahramani, Archipelago: Nonparametric Bayesian Semi-Supervised Learning
Presenter: Lu Ren, Presentation
4 September 2009
F. Doshi-Velez, K.T. Miller, J. Van Gael and Y.W. Teh, Variational Inference for the Indian Buffet Process
Presenter: John Paisley, Presentation
11 September 2009
N.D. Lawrence and R. Urtasun, Non-linear Matrix Factorization with Gaussian Processes
Presenter: Eric Wang, Presentation
18 September 2009
H. Lee, R. Grosse, R. Ranganath, A.Y. Ng, Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations
Presenter: Mingyuan Zhou, Presentation
25 September 2009
A. Beygelzimer, S. Dasgupta and John Langford, Importance Weighted Active Learning
Presenter: Lingbo Li, Presentation
2 October 2009
F. Doshi-Velez and Z. Ghahramani, Accelerated Sampling for the Indian Buffet Process
Presenter: John Paisley, Presentation
16 October 2009
P. Liang, M.I. Jordan and D. Klein, Learning From Measurements in Exponential Families
Presenter: Haojun Chen, Presentation
23 October 2009
L. Xu, M. White and D. Schuurmans, Optimal Reverse Prediction: A Unified Perspective on Supervised, Unsupervised and Semi-supervised Learning
Presenter: Chunping Wang, Presentation
30 October 2009
M.J. Choi, V. Chandrasekaran and A.S. Willsky, Exploiting Sparse Markov and Covariance Structure in Multiresolution Models
Presenter: Minhua Chen, Presentation
13 November 2009
K. Yu, J. Lafferty, S. Zhu, Y. Gong, Large-Scale Collaborative Prediction Using a Nonparametric Random Effects Model
Presenter: Xuejun Liao, Presentation
20 November 2009
K.A. Heller and Y.W. Teh and D. Gurur, Infinite Hierarchical Hidden Markov Models
Presenter: Lu Ren, Presentation
18 December 2009
F. Wood and Y.W. Teh, A Hierarchical Nonparametric Bayesian Approach to Statistical Language Model Domain Adaptation
Presenter: Mingyuan Zhou, Presentation
5 January 2010
Y.W. Teh, A Bayesian Interpretation of Interpolated Kneser-Ney
R. Thibaux and M.I. Jordan, Hierarchical Beta Processes and the Indian Buffet Process
Y.W. Teh and D. Gurur, Indian Buffet Processes with Power-Law Behavior
Presenter: L. Carin, Presentation
15 January 2010
J. Ghosh and D.B. Dunson, Default Priors and Efficient Posterior Computation in Bayesian Factor Analysis
Presenter: Eric Wang, Presentation
22 January 2010
D. Hsu, S.M. Kakade, J. Langford and T. Zhang, Multi-Label Prediction via Compressed Sensing
Presenter: Lingbo Li, Presentation
29 January 2010
H.F. Lopes, E. Salazar and D. Gamerman, Spatial Dynamic Factor Analysis
Presenter: Zhengming.Xing, Presentation
12 February 2010
P.J. Green and D.I. Hastie, Reversible Jump MCMC
Presenter: Miao Liu, Presentation
19 February 2010
K. Bush and J. Pineau, Manifold Embeddings for Model-Based Reinforcement Learning Under Partial Observability
Presenter: Chenghui Cai, Presentation
26 February 2010
J. Luttinen and A. Ilin, Variational Gaussian-Process Factor Analysis for Modeling Spatio-Temporal Data
Presenter: Bo Chen, Presentation
5 March 2010
H.M. Wallach, D. Minno and A. McCullum, Rethinking LDA: Why Priors Matter
Presenter: Eric Wang, Presentation
12 March 2010
E.B. Fox, E.B. Sudderth, M.I. Jordan and A.S. Willsky, Sharing Features Among Dynamical Systems With Beta Processes
Presenter: Haojun Chen, Presentation
19 March 2010
C. Wang and D.M. Blei, Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process
Presenter: Chunping Wang, Presentation
2 April 2010
T. Iwata, T. Yamada and N. Ueda, Modeling Social Annotation Data With Content Relevance Using a Topic Model
Presenter: Jorge Silva, Presentation
9 April 2010
J. Mairal, F. Bach, J. Ponce, G. Sapiro and A. Zisserman, Non-Local Sparse Models for Image Restoration
Presenter: Mingyuan Zhou, Presentation
16 April 2010
O-A. Maillard and R. Munos, Compressed Least-Squares Regression
Presenter: Minhua Chen, Presentation
23 April 2010
S. Gould, T. Gao and D. Koller, Region-Based Segmentation and Object Detection
Presenter: Eric Wang, Presentation
30 April 2010
F. Doshi-Velez, The Infinite Partially Observable Markov Decision Process
Presenter: Xuejun Liao, Presentation
7 May 2010
H. Lee, Y. Largman, P. Pham and A.Y. Ng, Unsupervised Feature Learning for Audio Classification Using Convolutional Deep Belief Networks
Presenter: Bo Chen, Presentation
14 May 2010
D. Krishnan and R. Fergus, Fast Image Deconvolution Using Hyper-Laplacian Priors
Presenter: Zhengming.Xing, Presentation
21 May 2010
A.C. Courville, D. Eck and Y. Bengio, An Infinite Factor Modeling Hierarchy via a Noisy-Or Mechanism
Presenter: Lingbo Li, Presentation
28 May 2010
Y. Chen, M. Kapralpw, D. Pavlov and J.E. Canny, Factor Modeling for Advertisement Targeting
Presenter: Miao Liu, Presentation
4 June 2010
K.T. Miller, T.L. Griffiths and M.I. Jordan, Nonparametric Latent Feature Models for Link Prediction
Presenter: Minhua Chen, Presentation
11 June 2010
R. Jenatton, J. Mairal, G. Obozinski and F. Bach, Proximal Methods for Sparse Hierarchical Dictionary Learning
Presenter: Bo Chen, Presentation
18 June 2010
P. Smaragdis, M. Shashanka and B. Raj, A Sparse Non-Parametric Approach for Single Channel Separation of Known Sounds
Presenter: Priyadip Ray, Presentation
25 June 2010
V. Rao and Y.W. Teh, Spatial Normalized Gamma Processes
Presenter: Eric Wang, Presentation
2 July 2010
M.N. Schmidt, Linearly Constrained Bayesian Matrix Factorization for Blind Source Separation
Presenter: Jorge Silva, Presentation
9 July 2010
R.P. Adams, H.M. Wallach and Z. Ghahramani, Learning the Structure of Deep Sparse Graphical Models
Presenter: Zhengming Xing, Presentation
16 July 2010
P. Rai and H. Daume III, Model-Label Prediction via Sparse Infinite CCA
Presenter: Lingbo Li, Presentation
23 July 2010
S. Bengio, F. Pereira, Y. Singer and D. Strelow, Group Sparse Coding
Presenter: Miao Liu, Presentation
30 July 2010
J. Vanhatalo, P. Jylanki and A. Vehtari, Gaussian Process Regression With Student-t Likelihood
Presenter: Minhua Chen, Presentation
6 August 2010
S.-H. Yang, H. Zha and B.-G. Hu, Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora
Presenter: Haojun Chen, Presentation
13 August 2010
L. Zhu, Y. Chen, W. Freeman and A. Torralba, Nonparametric Bayesian Texture Learning and Synthesis
Presenter: Eric Wang, Presentation
20 August 2010
Y.L. Boureau, F. Bach, Y. LeCun and J. Ponce, Learning Mid-Level Features for Recognition
Presenter: Bo Chen, Presentation
3 September 2010
J. Yang, K. Yu and T. Huang, Supervised Translation-Invariant Sparse Coding
Presenter: Jorge Silva, Presentation
10 September 2010
R. Jenatton, G. Obozinski and F. Bach, Structured Sparse Principal Component Analysis
Presenter: Xuejun Liao, Presentation
17 September 2010
K. Yu, T. Zhang and Y. Gong, Nonlinear Learning Using Local Coordinate Coding
K. Yu and T. Zhang, Improved Local Coordinate Coding Using Local Tangents
J. Wang, J. Yang, K. Yu, F. Lv, T. Huang and Y. Gong, Locality-Constrained Linear Coding for Image Classification
Presenter: Mingyuan Zhou, Presentation
24 September 2010
M.D. Hoffman, D.M. Blei and P.R. Cook, Bayesian Nonparametric Matrix Factorization for Recorded Music
Presenter: Lu Ren, Presentation
1 October 2010
A. Rodriguez, D.B. Dunson and A.E. Gelfand, Latent Stick-Breaking Processes
Presenter: Esther Salazar, Presentation
8 October 2010
R. Yoshida and M.West, Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing
Presenter: Miao Liu, Presentation
15 October 2010
C.M. Carvalho, N.G. Polson and J.G. James, The horseshoe estimator for sparse signals
Presenter: Eric Wang, Presentation
22 October 2010
J. Chang and D.M. Blei, Hierarchical Relational Models for Document Networks
Presenter: Haojun Chen, Presentation
5 November 2010
J. Friedman, T. Hastie and R. Tibshirani, Sparse Inverse Covariance Estimation with the Graphical Lasso
N. Stadler and P. Buhlmann, Missing Values: Sparse Inverse Covariance Estimation and an Extension to Sparse Regression
O. Banerjee, L. El Ghaoui and A. d’Aspremont, Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
N. Meinshausen and P. Buhlmann, High-Dimensional Graphs and Variable Selection with the Lasso
Presenter: Minhua Chen, Presentation
17 November 2010
N. Bartlett, D. Pfau, F. Wood, Forgetting Counts: Constant Memory Inference for a Dependent Hierarchical Pitman-Yor Process
Presenter: Yingjian Wang, Presentation
24 November 2010
R.P. Adams, Z. Ghahramani and M.I. Jordan, Tree-Structured Stick Breaking Processes for Hierarchical Data
Presenter: XianXing Zhang, Presentation
3 December 2010
Y.L. Boureau, J. Ponce and Y. LeCun, A Theoretical Analysis of Feature Pooling in Visual Recognition
Presenter: Bo Chen, Presentation
13 December 2010
K. Jarrett, K. Kavukcuoglu, M.A. Ranzato and Y. LeCun, What is the Best Multi-Stage Architecture for Object Recognition?
Presenter: Lingbo Li, Presentation
20 December 2010
N. Joshi and M. Brady, Non-Parametric Mixture Modeling Based Evolution of Level Sets and Application to Medical Images
Presenter: Lu Ren, Presentation
7 January 2011
J. Zhu, A. Ahmed and E.P. Xing, MedLDA: Maximum Margin Supervised Topic Models for Regression and Classification
Presenter: Haojun Chen, Presentation
14 January 2011
J. Zhu and E.P. Xing, Conditional Topic Random Fields
Presenter: Eric Wang, Presentation
21 January 2011
J. Gasthaus, F. Wood, Yee Whye Teh, Lossless Compression Based on the Sequence Memoizer
Presenter: Yingjian Wang, Presentation
18 February 2011
N. Srebro and T. Jaakkola, Weighted Low-Rank Approximations
Presenter: Mingyuan Zhou , Presentation
25 February 2011
A. Torralba, K.P. Murphy and W.T. Freeman, Sharing Visual Features for Multiclass and Multiview Object Detection
Presenter: Jorge Silva, Presentation
4 March 2011
A. McCallum, X. Wang and A. Corrada-Emmanuel, Topic and Role Discovery in Social Networks with Experiments on Enron and Academic Email
Presenter: Miao Liu, Presentation
11 March 2011
F. Lin and W.W. Cohen, Power Iteration Clustering
Presenter: Minhua Chen, Presentation
25 March 2011
Y. Zhang and J. Schneider, Learning Multiple Tasks with a Sparse Matrix-Normal Prior
Presenter: Esther Salazar, Presentation
1 April 2011
K. Kavukcuoglu, P. Sermanet, Y.L. Boureau, K. Gregor, M. Mathieu, Y. LeCun, Learming Convolutional Feature Hierarchies for Visual Recognition
Presenter: Bo Chen, Presentation
8 April 2011
J. Mairal, F. Bach, J. Ponce, G. Sapiro, Online Learning for Matrix Factorization and Sparse Coding
Presenter: Haojun Chen, Presentation
15 April 2011
M.D. Hoffman, D.B. Blei and F. Bach, Online Learning for Latent Dirichlet Allocation
Presenter: Lingbo Li, Presentation
22 April 2011
J. Leskovec, D. Chakrabarti, J. Kleinberg, C. Faloutsos, Z. Ghahramani, Kronecker Graphs: An Approach to Modeling Networks
Presenter: Eric Wang, Presentation
29 April 2011
A. Canale and D.B. Dunson, Bayesian Kernel Mixtures for Counts
Presenter: Yingjian Wang, Presentation
6 May 2011
H. Ishwaaran and J.S. Rao, Spike and Slab Variable Selection: Frequentist and Bayesian Strategies
Presenter: Minhua Chen, Presentation
13 May 2011
K. Weinberger and O. Chapelle, Large Margin Taxonomy Embedding with an Application to Document Categorization
Presenter: Jorge Silva, Presentation
20 May 2011
S. Bengio, J. Weston and D. Grangier, Label Embedding Trees for Large Multi-Class Tasks
Presenter: Zhengming Xing, Presentation
3 June 2011
D. Lin, E. Grimson and J. Fisher, Construction of Dependent Dirichlet Processes Based on Poisson Processes
Presenter: Yingjian Wang, Presentation
10 June 2011
R. Salakhutdinov, J. Tenenbaum and A. Torralba, One-Shot Learning with a Hierarchical Nonparametric Bayesian Model
Presenter: Esther Salazar, Presentation
17 June 2011
A. Coates, H. Lee and A.Y. Ng, An Analysis of Single-Layer Networks in Unsupervised Feature Learning
A. Coates and A.Y. Ng, The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization
Presenter: Mingyuan Zhou, Presentation
24 June 2011
J. Kallsen and P. Tankovy, Characterization of Dependence of Multidimensional Lévy Processes Using Lévy Copulas
Presenter: Yingjian Wang, Presentation
8 July 2011
A.L. Chambers, P. Smyth and M. Steyvers, Learning Concept Graphs from Text with Stick-Breaking Priors
Presenter: Lingbo Li, Presentation
15 July 2011
J. Paisley, C. Wang and D. Blei, The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling
Presenter: Minhua Chen, Presentation
25 July 2011
B.P. Carlin and A. E. Gelfand, An Iterative Monte Carlo Method for Nonconjugate Bayesian Analysis
P. Muller, A Generic Approach to Posterior Integration and Gibbs Sampling
J.S. Liu, Metropolized Independent Sampling with Comparisons to Rejection Sampling and Importance Sampling
Presenter: Mingyuan Zhou, Presentation
5 August 2011
A. Ahmed and E.P. Xing, Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream
Presenter: Bo Chen, Presentation
12 August 2011
R. M. Neal, Slice Sampling
Presenter: Priyadip Ray, Presentation
19 August 2011
C.M. Carvalho, H.F. Lopes, N.G. Polson and M.A. Taddy, Particle Learning for General Mixtures
N. Chopin, A. Iacobucci, J.-M. Marin, K. L. Mengersen, C. P. Robert, R. Ryder, and C. Schafer, On Particle Learning
Presenter: Miao Liu, Presentation
26 August 2011
I. Sutskever, R. Salakhutdinov, J.B. Tenenbaum, Modeling Relational Data Using Bayesian Clustered Tensor Factorization
Presenter: Esther Salazar, Presentation
2 September 2011
A.P. Singh and G.J. Gordon, A Bayesian Matrix Factorization Model for Relational Data
A.P. Singh and G.J. Gordan, Relational Learning via Collective Matrix Factorization
Presenter: XianXing Zhang, Presentation
16 September 2011
S. Williamson, C. Wang, K.A. Heller and D.M. Blei, The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling
Presenter: Eric Wang, Presentation
23 September 2011
L.-J. Li, C. Wang, Y. Lim, D.M. Blei, L. Fei-Fei, Building and Using a Semantivisual Image Hierarchy
Presenter: Lingbo Li, Presentation
3 October 2011
A. Geramifard, F. Doshi, J. Redding, N. Roy, and J.P. How, Online Discovery of Feature Dependencies
Presenter: Xuejun Liao, Presentation
10 October 2011
M. Dud´ık, J. Langford and L. Li, Doubly Robust Policy Evaluation and Learning
Presenter: Miao Liu, Presentation
17 October 2011
M. Welling and Y.W. Teh, Bayesian Learning via Stochastic Gradient Langevin Dynamics
Presenter: David Carlson, Presentation
26 October 2011
F. Doshi-Velez, D. Wingate, J. Tenenbaum and N. Roy, Infinite Dynamic Bayesian Networks
Presenter: Mingyuan Zhou, Presentation
4 November 2011
D.L. Donoho, A. Maleki and A. Montanari, Message Passing Algorithms for Compressed Sensing: I. Motivation and Construction
D.L. Donoho, A. Maleki and A. Montanari, Message Passing Algorithms for Compressed Sensing: II. Analysis and Validation
Presenter: Nate Strawn, Presentation
11 November 2011
A. Banerjee, D. Dunson and S. Tokdar, Efficient Gaussian Process Regression for Large Data Sets
Presenter: Priyadip Ray, Presentation
18 November 2011
L. Wang and D.B. Dunson, Fast Bayesian Inference in Dirichlet Process Mixture Models
Presenter: Esther Salazar, Presentation
2 December 2011
A. Agovic, A. Banarjee and S. Chatterjee, Probabilistic Matrix Addition
Presenter: Lingbo Li, Presentation
9 December 2011
J. Zhu and T. Hastie, Kernel Logistic Regression and the Import Vector Machine
Presenter: Ding Mingtao, Presentation
16 December 2011
F. Liang, K. Miao, M. Liao, S. Mukherjee and M. West, Nonparametric Bayesian Kernel Models
Presenter: Yingjian Wang, Presentation
13 January 2012
Z. Zhang, G. Dai and M.I. Jordan, Bayesian Generalized Kernel Mixed Models
Presenter: Priyadip Ray, Presentation
20 January 2012
N.S. Pillai, Q. Wu, F. Liang, S. Mukherjee andR.L. Wolpert,Characterizing the Function Space for Bayesian Kernel Models
Presenter: Mingyuan Zhou, Presentation
27 January 2012
L. Zhang, C. Chen, J. Bu, D. Cai, X. He, T.S. Huang, Active Learning Based on Locally Linear Reconstruction
Presenter: Minhua Chen, Presentation
3 February 2012
N. Friedman and D. Koller, Being Bayesian About Network Structure: A Bayesian Approach to Structure Discovery in Bayesian Networks
Presenter: XianXing Zhang, Presentation
10 February 2012
N.G. Polson and J.G. Scott, Local Shrinkage Rules, Levy Processes, and Regularized Regression
Presenter: David Carlson, Presentation
17 February 2012
M. Kolar, J. Lafferty and L. Wasserman, Union Support Recovery in Multi-task Learning
Presenter: Shaobo Han, Presentation
2 March 2012
Y. Hitomi, J. Gu, M. Gupta, T. Mitsunaga and S. K. Nayar, Video from a Single Coded Exposure Photograph using a Learned Over-Complete Dictionary
Presenter: Ajit Rajwade, Presentation
9 March 2012
M. Harel and S. Mannor, Learning from Multiple Outlooks
B. Kulis, K. Saenko and T. Darrel, What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
Presenter: Minhua Chen, Presentation
16 March 2012
A. Armagan, D.B. Dunson and J. Lee, Generalized double Pareto shrinkage
Presenter: Esther Salazar, Presentation
30 March 2012
A. Bhattacharya and D.B. Dunson, Sparse Bayesian infinite factor models
Presenter: XianXing Zhang, Presentation
6 April 2012
E. Grave, G. Obozinski and F. Bach, Trace Lasso: a trace norm regularization for correlated designs
Presenter: Zhengming Xing, Presentation
13 April 2012
H. Rue and S. Martino, Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
Presenter: Esther Salazar, Presentation
20 April 2012
O. Dikmen and C. Fevotte, Nonnegative Dictionary Learning in the Exponential Noise Model for Adaptive Music Signal Representation
Presenter: Ding Mingtao, Presentation
7 May 2012
F. Niu, B. Recht, C. Re and S.J. Wright, A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
Presenter: David Carlson, Presentation
14 May 2012
Z. James, X. Hao Xu and P.J. Ramadge, Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries
Presenter: David Lue, Presentation
21 May 2012
A.C. Sankaranarayanan, P.K. Turaga, R. Chellappa, and R.G. Baraniuk, Compressive Acquisition of Dynamical Scenes
Presenter: Ajit Rajwade, Presentation
4 June 2012
T. Zhou, H. Shan, A. Banerjee, G. Sapiro, Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information
Presenter: Jorge Silva, Presentation
11 June 2012
A. Rodriguez and K. Ghosh, Nested Partition Models
Presenter: Esther Salazar, Presentation
18 June 2012
D. Zoran and Y, Weiss, From Learning Models of Natural Image Patches to Whole Image Restoration
Presenter: Eric Wang, Presentation
6 July 2012
Z. Xu, F. Yan and Y. Qi, Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data Analysis
Presenter: Joe Ryu, Presentation
13 July 2012
Z. Yang, C. Zhang and L. Xie, Robustly Stable Signal Recovery in Compressed Sensing with Structured Matrix Perturbation
Presenter: Minhua Chen, Presentation
20 July 2012
P. Bachman and D. Precup, Improved Estimation in Time Varying Models
Presenter: Zhengming Xing, Presentation
27 July 2012
G. Brown, A. Pocock, M.-J. Zhao and M. Lujan, Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
Presenter: Wenzhao Lian, Presentation
3 August 2012
J. Bruna and S. Mallat, Invariant Scattering Convolution Networks
Presenter: Bo Chen, Presentation
15 August 2012
Y. Bachrach, T. Minka, J. Guiver and T. Graepel, How To Grade a Test Without Knowing the Answers: A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing
Presenter: David Carlson, Presentation
24 August 2012
J. Zhu, A. Ahmed, E.P. Xing, MedLDA: Maximum Margin Supervised Topic Models
Presenter: Zhengming Xing, Presentation
31 August 2012
A. Jalali and Sujay Sanghavi, Learning the Dependence Graph of Time Series with Latent Factors
Presenter: Xin Yuan, Presentation
7 September 2012
Y. Tang, R. Salakhutdinov and G. Hinton, Deep Mixtures of Factor Analysers
Presenter: Jianbo Yang, Presentation
14 September 2012
B. Cseke and T. Heskes, Improving Posterior Marginal Approximations in Latent Gaussian Models
B. Cseke and T. Heskes, Approximate Marginals in Latent Gaussian Models
Presenter: Shaobo Han, Presentation
21 September 2012
P. Sprechmann, A. Bronstein and G. Sapiro, Learning Efficient Structured Sparse Models
Presenter: Yingjian Wang, Presentation
28 September 2012
J. Zhu, Max-Margin Nonparametric Latent Feature Models for Link Prediction
Presenter: XianXing Zhang, Presentation
5 October 2012
C. Farabet, C. Couprie, L. Najman and Y. LeCun, Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers
Presenter: Bo Chen, Presentation
15 October 2012
T.P. Minka, R. Xiang and Y. Qi, Virtual Vector Machine for Bayesian Online Classification
Presenter: Lingbo Li, Presentation
24 October 2012
C. Chen, N. Ding and W. Buntine, Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling
Presenter: Mingyuan Zhou, Presentation
6 November 2012
R. Peharz and F. Pernkopf, Exact Maximum Margin Structure Learning of Bayesian Networks
Presenter: Miao Liu, Presentation
16 November 2012
Y. Shi and Fei Sha, Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation
Presenter: Liming Wang, Presentation
26 November 2012
N. Le Roux, M. Schmidt and F. Bach, A Stochastic Gradient Method with an Exponential Convergence Rate for Strongly-Convex Optimization with Finite Training Sets
Presenter: Miao Liu, Presentation
30 November 2012
C. Bracegirdle and D. Barber, Bayesian Conditional Cointegration
Presenter: Jianbo Yang
7 December 2012
J. Paisley, C. Wang, D.M. Blei and M.I. Jordan, Nested Hierarchical Dirichlet Processes
Presenter: David Carlson
14 December 2012
A. Joulin and F. Bach, A convex relaxation for weakly supervised classifiers
Presenter: Joe Ryu
21 December 2012
J. Paisley, D.M. Blei, M.I. Jordan, Variational Bayesian Inference with Stochastic Search
Presenter: Mingyuan Zhou
28 December 2012
M.J. Paul and M. Dredze, Factorial LDA: Sparse Multi-Dimensional Text Models
Presenter: Lingbo Li
4 January 2013
C. Wang and D. Blei, Truncation-free Stochastic Variational Inference for Bayesian Nonparametric Models
Presenter: XianXing Zhang
11 January 2013
I.J. Goodfellow, A. Courville and Y. Bengio, Large-Scale Feature Learning With Spike-and-Slab Sparse Coding
Presenter: Bo Chen
18 January 2013
A. Ahmed, S. Ravi, S.M. Narayanamurthy, A.J. Smola, FastEx: Hash Clustering with Exponential Families
Presenter: Shaobo Han
25 January 2013
D.I. Kim, M.C. Hughes and E.B. Sudderth, The Nonparametric Metadata Dependent Relational Model
Presenter: Zhengming Xing
1 February 2013
Y.J. Ko and M. Seeger, Large Scale Variational Bayesian Inference for Structured Scale Mixture Models
Presenter: Mingyuan Zhou
8 February 2013
S. Ahn, A. Korattikara and M. Welling, Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring
Presenter: David Carlson
15 February 2013
D. Mimno, M.D. Hoffman and D.M. Blei, Sparse stochastic inference for latent Dirichlet allocation
Presenter: Miao Liu
22 February 2013
K. Palla, D.A. Knowles and Z. Ghahramani, An Infinite Latent Attribute Model for Network Data
Presenter:
1 March 2013
P. Sarkar, D. Chakrabartiy and M.I. Jordan, Nonparametric Link Prediction in Dynamic Networks
Presenter:
8 March 2013
P. Pletscher and S. Wulff, LPQP for MAP: Putting LP Solvers to Better Use
Presenter:
15 March 2013
S. Balakrishnan, K. Puniyani and J. Lafferty, Sparse Additive Functional and Kernel CCA
Presenter:
22 March 2013
A. Spiliopoulou and A. Storkey, A Topic Model for Melodic Sequences
Presenter:
29 March 2013
R. Garnett, Y. Krishnamurthy, X. Xiong, J. Schneider and R. Mann, Bayesian Optimal Active Search and Surveying
Presenter:
5 April 2012
A. Kumar and H. Daume III, Learning Task Grouping and Overlap in Multi-Task Learning
Presenter:
12 April 2012
H. Liu, F. Han, M. Yuan, J. Lafferty and L. Wasserman, The Nonparanormal SKEPTIC
Presenter:
19 April 2012
M. Xu and J. Lafferty, Conditional Sparse Coding and Grouped Multivariate Regression
Presenter: