Reading Group
A. Corduneanu and C.M. Bishop, Variational Bayesian Model Selection for Mixture Distributions, AIStat01
Presenter: Shihao Ji, Presentation
M. Kuss and C. Rassmussen, Assessing Approximations for Gaussian Process Classification, NIPS 2005
Presenter: David Williams, Presentation
A. Niculescu-Mizil and R. Caruana, Learning the Structure of Related Tasks, NIPS 2005 workshop on inductive transfer.Presenter: Lihan He, Presentation
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
H. Ishwaran and L.F. James, Gibbs Sampling Methods for Stick-Breaking Priors
Presenter: Yuting Qi, Presentation
T.L. Griffiths and Z. Ghahramani, Infinite Latent Feature Models and the Indian Buffet Process
Presenter: Ya Xue, Presentation
E. Meeds and S. Osindero, Bayes Sets
Presenter: Qi An, Presentation
Y. Wang and Q. Ji, A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences
Presenter: Qiuhua Liu, Presentation
N. Mehta, S. Natarajan, P. Tadepalli and A. Fern, Transfer in Variable-reward Hierarchical Reinforcement Learning
Presenter:
J. Zhang, Z. Ghahramani, Y. Yang, Learning Multiple
Related Tasks using Latent Independent Component Analysis
Presenter:
O.L. Mangasarian and E.W. Wild, Multisurface
Proximal SVM Classification via Generalized Eigenvalues
Presenter:
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
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:
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
M. Szummer and T. Jaakkola, Partially Labeled Classification with Markov Random Walks
Presenter:
B. Wolfe, M.R. James and
Presenter:
D. Justice and A. Hero, A Binary Linear Programming Formulation of the Graph Edit Distance
Presenter: Shihao Ji, Presentation
X.L. Nguyen, M.J. Wainwright, M.I. Jordan, On Optimal
Quantization Rules for Sequential Decision Problems
Presenter: Qi An, Presentation
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:
D. Blei, J. Lafferty, Correlated Topic Models
Presenter:
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
D. Hähnel, D. Fox, W. Burgard, and
G. Grisetti, C. Stachniss, and
Presenter: Lihan He, Presentation
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:
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:
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
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:
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:
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:
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:
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:
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:
16 March 2007
T. De Bie and
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,
Presenter: Shihao Ji, Presentation
18 May 2007
F.R. Bach, D. Heckerman,
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
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
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
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
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
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
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
Presenter: Dehong Liu, Presentation
31 July 2009
R.P. Adams,
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