Reading Group

 

20 January 2006

A. Corduneanu and C.M. Bishop, Variational Bayesian Model Selection for Mixture Distributions, AIStat01

Presenter: Shihao Ji, Presentation

 

 

27 January 2006

M. Kuss and C. Rassmussen, Assessing Approximations for Gaussian Process Classification, NIPS 2005

Presenter: David Williams, Presentation

 

 

3 February 2006

A. Niculescu-Mizil and R. Caruana, Learning the Structure of Related Tasks, NIPS 2005 workshop on inductive transfer.
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

P. Hoff, Simulation of the matrix Bingham-von Mises-Fisher distribution, with applications to multivariate and relational data

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

 

 

27 November 2009

F. Wood and Y.W. Teh, A Hierarchical Nonparametric Bayesian Approach to Statistical Language Model Domain Adaptation

Presenter: Mingyuan Zhou

 

 

4 December 2009

J. Ghosh and D.B. Dunson, Default Priors and Efficient Posterior Computation in Bayesian Factor Analysis

Presenter: Eric Wang