| Apr 25, 2012 | Tea Talk | Hannes Bretschneider: |
| Apr 18, 2012 | Tea Talk | Maksims Volkovs: |
| Apr 11, 2012 | Tea Talk | Nitish Srivastava: |
| Apr 4, 2012 | Tea Talk | Jasper Snoek: |
| Mar 28, 2012 | Tea Talk | George Dahl: |
| Mar 21, 2012 | Tea Talk | Alex Krizhevsky: |
| Mar 14, 2012 | Tea Talk | Kevin Swersky: |
| Mar 7, 2012 | Tea Talk | Abdel-rahman Mohamed: |
| Feb 29, 2012 | Tea Talk | Tijmen Tieleman: |
| Feb 15, 2012 | Tea Talk | Nikola Karamanov: |
| Feb 8, 2012 | Tea Talk | Clement Chung: |
| Feb 1, 2012 | Tea Talk | Michael Leung: Online AUC Maximization
|
| Jan 25, 2012 | Tea Talk | Lei Jimmy Ba: The Hierarchical Beta Process for Convolutional Factor Analysis and
Deep Learning |
| Jan 18, 2012 | Tea Talk | Alex Graves, George Dahl, Jeroen Chua, Kevin Swersky: NIPS highlights |
| Jan 10, 2012 | Tea Talk | Hui Yuan Xiong: Accelerated Adaptive Markov Chain for Partition Function Computation
|
| Dec 6, 2011 | Tea Talk | James Martens: Quasi-Newton Markov chain Monte Carlo
|
| Nov 29, 2011 | Tea Talk | Yujia Li: Learning Multiple Tasks using Manifold Regularization
|
| Nov 22, 2011 | Tea Talk | Boyko Kakaradov: Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees
|
| Nov 15, 2011 | Tea Talk | Laurent Charlin: Active Learning with Feedback on Both Features and Instances
|
| Nov 8, 2011 | Tea Talk | Volodymyr Mnih: Efficient Learning of Sparse, Distributed, Convolutional Feature
Representations for Object Recognition |
| Nov 1, 2011 | Tea Talk | Cecilia Chen Liu: Cascade Object Detection with Deformable Part Models |
| Oct 25, 2011 | Tea Talk | Navdeep Jaitly: Using DBNs for speech recognition at Google |
| Oct 12, 2011 | Tea Talk | Jeoren Chua: Object recognition with hierarchical stel models |
| Oct 5, 2011 | Tea Talk | Charlie Tang: Learning hierarchical invariant spatio-temporal features for action recognition
with independent subspace analysis |
| Sep 26, 2011 | Tea Talk | Ilya Sutskever: Bayesian Learning via Stochastic Gradient Langevin Dynamics |
| Sep 19, 2011 | Tea Talk | Danny Tarlow: Perturb-and-MAP Random Fields: Using Discrete Optimization to Learn
and Sample from Energy Models, |
| Jun 22, 2011 | Tea Talk | James Martens: ICML practice talk: Training Recurrent Neural Networks with Hessian-Free Optimization |
| Jun 15, 2011 | Tea Talk | Mohamad Norouzi and Ilya Sutskever: ICML Practice talks:
Minimal Loss Hashing for Compact Binary Codes, and Generating Text with Recurrent Neural Networks
|
| Jun 8, 2011 | Tea Talk | Alex Shestopaloff: A quasi-Monte Carlo Metropolis algorithm |
| May 25, 2011 | Tea Talk | Charlie Tang: The Importance of Encoding Versus Training with Sparse Coding
and Vector Quantization |
| May 18, 2011 | Tea Talk | Patrick Li: One-class SVM for Learning in Image Retrieval |
| May 4, 2011 | Tea Talk | Marc'Aurelio Ranzato: Non-local sparse models for image restoration |
| Apr 27, 2011 | Tea Talk | No Cookies Talk: |
| Apr 20, 2011 | Tea Talk | Tijmen Tieleman:
Learning to Parse Images |
| Apr 13, 2011 | Tea Talk | Jeroen Chua: Object recognition with hierarchical stel models
|
| Apr 6, 2011 | Tea Talk | Hugo Larochelle: SampleRank: Learning Preferences from Atomic Gradients |
| Mar 30, 2011 | Tea Talk | Leo Lee: Analysis and design of RNA sequencing experiments for identifying
isoform regulation |
| Mar 23, 2011 | Tea Talk | Inmar Givoni: How Kinect works |
| Mar 16, 2011 | Tea Talk | No cookies talk: |
| Mar 9, 2011 | Tea Talk | Danny Tarlow: Learning programs: a hierarchical Bayesian approach.Learning programs: a hierarchical Bayesian approach. |
| Mar 2, 2011 | Tea Talk | Maksims Volkovs: Fast approximation of the permanent for very dense problems |
| Feb 23, 2011 | Tea Talk | Volodymyr Mnih: An Analysis of Single-Layer Networks in Unsupervised Feature Learning |
| Feb 16, 2011 | Tea Talk | James Martens: Direct Loss Minimization for Structured Prediction |
| Feb 9, 2011 | Tea Talk | Alex Krizhevsky: Tiered Scene Labeling with Dynamic Programming |
| Feb 2, 2011 | Tea Talk | No cookies talk this week: |
| Jan 26, 2011 | Tea Talk | Nevena Lazic: Multiple Patterns of Sensitization in Relation to Asthma
in a Birth Cohort Study |
| Jan 19, 2011 | Tea Talk | Nikola Karamanov: Layered Image
Motion with Explicit Occlusions, Temporal Consistency, and Depth
Ordering |
| Jan 12, 2011 | Tea Talk | Ilya Sutskever: Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks |
| Dec 1, 2010 | Tea Talk | Hui Yuan Xiong: Integrative Modeling Defines the Nova Splicing-Regulatory Network and Its Combinatorial Controls
Zhang et al. |
| Nov 24, 2010 | Tea Talk | Boyko Kakaradov: Robust Principal Component Analysis? |
| Nov 17, 2010 | Tea Talk | Ilya Sutskever: Maximin affinity learning of image segmentation |
| Nov 3, 2010 | Tea Talk | George Dahl: "Word representations: A simple and general method for semi-supervised learning"
|
| Oct 27, 2010 | Tea Talk | Inmar Givoni: Norm-Product Belief Propagation : Primal-Dual Message Passing for
Approximate Inference
http://arxiv.org/abs/0903.3127 |
| Oct 20, 2010 | Tea Talk | Ulrik Beierholm: Bayes-Optimal Human Decisions in a Reinforcement Learning Task |
| Oct 13, 2010 | Tea Talk | Danny Tarlow: A Linear Programming Approach to Max-sum Problem: A Review. |
| Oct 6, 2010 | Tea Talk | Marc'Aurelio Ranzato: Non-local sparse models for image restoration |
| Sep 29, 2010 | Tea Talk | Makims Volkovs: LambdaMART |
| Sep 22, 2010 | Tea Talk | Laurent Charlin: A fast natural Newton method |
| Sep 15, 2010 | Tea Talk | Patrick Li: Convex Clustering |
| Sep 8, 2010 | Tea Talk | Alex Krizhevsky: Context-Aware Saliency Detection |
| Sep 1, 2010 | Tea Talk | Clement Chung: Proteome Coverage Prediction with Infinite Markov Models
|
| Aug 25, 2010 | Tea Talk | Amit Gruber: Mixed Membership Matrix Factorization |
| Aug 18, 2010 | Tea Talk | Nikola Karamanov: Layered Object Detection for Multi-Class Segmentation
|
| Aug 4, 2010 | Tea Talk | Ilya Sutskever: Deconvolutional Networks
|
| Jul 28, 2010 | Tea Talk | Leo Lee: A dynamic Bayesian network for identifying protein-binding footprints
from single molecule-based sequencing data
|
| Jul 21, 2010 | Tea Talk | Abdel-rahman Mohamed: A spectral algorithm for learning hidden markov models
|
| Jul 14, 2010 | Tea Talk | Vlad Mnih: Nonlinear Learning using Local Coordinate Coding
|
| Jul 7, 2010 | Tea Talk | Tijmen Tieleman: Parametric Herding
|
| Jun 30, 2010 | Tea Talk | Ryan Prescott Adams: Collective dynamics in human and monkey sensorimotor cortex: predicting single neuron
spikes |
| Jun 23, 2010 | Tea Talk | Josh Susskind: Matching expression variant faces |
| Jun 16, 2010 | Tea Talk | Navdeep Jaitly : Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
|
| Jun 9, 2010 | Tea Talk | Ilya Sutskever: Learning Efficiently with Approximate Inference via Dual Losses.
|
| Jun 2, 2010 | Tea Talk | Yoseph Barash: Genovo: De Novo Assembly For Metagenomics
|
| May 26, 2010 | Tea Talk | Tyler Lu: Cluster Analysis of Heterogeneous Rank Data
|
| May 19, 2010 | Tea Talk | James Martens: Learning with Blocks: Composite Likelihood and Contrastive Divergence
|
| May 12, 2010 | Tea Talk | Amit Gruber: Nonparametric Latent Feature Models for Link Prediction |
| May 5, 2010 | Tea Talk | Patrick Li: Finding Scientific Topics |
| Apr 28, 2010 | Tea Talk | Inmar Givoni: Image Segmentation with A Bounding Box Prior
|
| Apr 21, 2010 | Tea Talk | Vinod Nair: Attribute and Simile Classifiers for Face Verification
|
| Apr 14, 2010 | Tea Talk | Marc'Aurelio Ranzato: The Role of Features, Algorithms and Data in Visual Recognition
|
| Apr 7, 2010 | Tea Talk | Maks Volkovs: Expected Reciprocal Rank for Graded Relevance |
| Mar 31, 2010 | Tea Talk | Laurent Charlin: Learning CRFs using Graph Cuts
|
| Mar 24, 2010 | Tea Talk | Iain Murray: Robust Markov chain Monte Carlo methods for spatial generalized linear mixed models |
| Mar 17, 2010 | Tea Talk | George Dahl: Rank-Approximate Nearest Neighbor Search:
Retaining Meaning and Speed in High Dimensions |
| Mar 10, 2010 | Tea Talk | Clement Chung: Clustering Sequence Sets for Motif Discovery |
| Feb 24, 2010 | Tea Talk | Nikola Karamanov: "Statistical correlations between two-dimensional images and
three-dimensional structures in natural scenes" |
| Feb 17, 2010 | Tea Talk | Eddie Ng: "The Wapred Gaussian Processes" by Ed Snelson, Carl Rasmussen, and Zoubin Ghahramani |
| Feb 10, 2010 | Tea Talk | Ilya Sutskever: Auto-association by multilayer perceptrons and singular value decomposition
H Bourlard, Y Kamp |
| Jan 27, 2010 | Tea Talk | Hugo Larochelle: A High-Throughput Screening Approach to Discovering Good Forms of
Biologically-Inspired Visual Representation.
by Nicolas Pinto, David Doukhan, James J. DiCarlo, David D. Cox
|
| Jan 20, 2010 | Tea Talk | Leo Lee: "Statistical inferences for isoform
expression in RNA-Seq" by Jiang and Wong, Bioinformatics 2009
25(8):1026-1032. |
| Dec 2, 2009 | Tea Talk | Tijmen Tieleman: Convolutional deep belief networks for scalable unsupervised learning
of hierarchical representations
by Honglak Lee, Roger Grosse, Rajesh Ranganath and Andrew Y. Ng. |
| Nov 25, 2009 | Tea Talk | Arnold Binas: "Fast Solvers and Efficient Implementations for Distance Metric Learning" by Kilian Q. Weinberger and Lawrence K. Saul |
| Nov 18, 2009 | Tea Talk | Tanya Schmah: Dense Image Registration through MRFs and Efficient Linear Programming
B. Glocker, N. Komodakis, G. Tziritas, N. Navab, N. Paragios
Medical Image Analysis, Volume 12, Issue 6, December 2008, pp. 731-741 |
| Nov 11, 2009 | Tea Talk | Josh Susskind: B. Theobald, Iain Matthews, Jeffrey Cohn, and S. Boker, "Real-time
expression cloning using active appearance models," Proceedings of the
ACM International Conference on Multimodal Interfaces (ICMI'07), 2007,
pp. 134 - 139. |
| Nov 4, 2009 | Tea Talk | Martin Renqiang Min: large margins in
deep learning and my previous experience on learning large-margin
classifiers for gene expression data analysis in a deep learning framework.
R. Min, D. A. Stanley, Z. Yuan, A. Bonner, and Z. Zhang.
A Deep Non-Linear Feature Mapping for Large-Margin kNN Classification.
IEEE International Conference on Data Mining (ICDM 2009).
|
| Oct 28, 2009 | Tea Talk | Danny Tarlow: Joint optimization of segmentation and appearance models
Sara Vicente, Vladimir Komogorov, Carsten Rother |
| Oct 21, 2009 | Tea Talk | Ben Marlin: Max Margin Restricted Boltzmann Machines. |
| Oct 14, 2009 | Tea Talk | Clement Chung: Markov clustering versus affinity propagation for the partitioning of
protein interaction graphs
by James Vlasblom and Shoshana J Wodak |
| Sep 23, 2009 | Tea Talk | George Dahl: Nearest Neighbors in High-Dimensional Data: The Emergence and
Influence of Hubs, by Milos Radovanovic, Alexandros Nanopoulos and Mirjana Ivanovic |
| Sep 16, 2009 | Tea Talk | Jasper Snoek: Healing the Relevance Vector Machine through Augmentation, by Carl
Rasmussen and Joaquin Quinonero-Candela |
| Sep 9, 2009 | Tea Talk | Vlad Mnih: Integrating CUDA into python, by Vlad Mnih |
| Sep 2, 2009 | Tea Talk | David Warde-Farley: Herding Dynamic Weights to Learn, by Max Welling |
| Aug 26, 2009 | Tea Talk | Alex Krizhevsky: Recent results on training
autoencoders for image retrieval, by Alex Krizhevsky |
| Aug 19, 2009 | Tea Talk | Maksims Volkovs: Bayesian inference for Plackett-Luce ranking models, by Guiver and Esnelson |
| Aug 12, 2009 | Tea Talk | Hugo Larochelle: Emergence of complex cell
properties by learning to
generalize in natural scenes, by Yan Karklin & Michael S. Lewicki |
| Jul 29, 2009 | Tea Talk | Ilya Sutskever: Spectral Hashing, by Weiss, Torralba, and Fergus, |
| Jul 22, 2009 | Tea Talk | Iain Murray: Split variational inference, by by Bouchard, G. and Zoeter, O. |
| Jul 15, 2009 | Tea Talk | James Martens: Curriculum Learning |
| Jul 8, 2009 | Tea Talk | Marc'Aurelio Ranzato: Learning features by contrasting natural images with noise. Proc. Int. Conf. on Artificial Neural Networks,
by Limassol, Cyprus, 2009. |
| Jun 10, 2009 | Tea Talk | Sonya Allin: Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia,
|
| May 20, 2009 | Tea Talk | Vincent Cheung:
Epitomic location recognition |
| May 13, 2009 | Tea Talk | Jim Huang: Factorial mixture of Gaussians and the marginal independence model.
Silva, R. and Ghahramani, Z |
| Apr 29, 2009 | Tea Talk | Ilya Sutskever: Linear spatial pyramid matching using sparse coding for image classification
by Yang, Yu, Gong, and Huang |
| Apr 22, 2009 | Tea Talk | Maks Volkvos: COFIRANK - Maximum Margin Matrix Factorization for Collaborative Ranking |
| Apr 15, 2009 | Tea Talk | Ilya Sutskever: Backpropagation can train sigmoid belief networks. |
| Apr 8, 2009 | Tea Talk | Arnold Binas: "Fast Solvers and Efficient Implementations for Distance Metric Learning" |
| Apr 1, 2009 | Tea Talk | Laurent Charlin: A Joint Model of Text and Aspect Ratings for Sentiment Summarization |
| Mar 25, 2009 | Tea Talk | Vlad Mnih: "Topmoumoute online natural gradient algorithm"
by Le Roux, Manzagol, Bengio. |
| Mar 18, 2009 | Tea Talk | Geoff Hinton: Robust Object Recognition with Cortex-Like Mechanisms,
by Thomas Serre, Lior Wolf, Stanley Bileschi, Maximilian Riesenhuber, and Tomaso Poggio
|
| Mar 11, 2009 | Tea Talk | George Dahl
:
Efficient auditory coding
by Smith and Lewicki |
| Mar 4, 2009 | Tea Talk | Ilya Sutskever: Representing structured knowledge using hierarchical Bayesian models. |
| Feb 25, 2009 | Tea Talk | Eddie Ng: Most Likely Heteroscedastic Gaussian Process Regression
By Kersting, Plagemann, Pfaff, and Burgard. |
| Feb 11, 2009 | Tea Talk | Andriy Mnih: Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression.,
by David Mimno and Andrew McCallum |
| Feb 4, 2009 | Tea Talk | Ruslan Salakhutdinov: Fixing max-product: Convergent message passing algorithms for MAP LP-relaxations, by Amir Globerson , Tommi Jaakkola
|
| Jan 21, 2009 | Tea Talk | David Warde-Farley: Efficient Inference in Phylogenetic InDel Trees by Bouchard-Cote, Jordan, and Klein.
|
| Jan 14, 2009 | Tea Talk | Jasper Snoek: Histograms of Oriented Gradients for Human Detection by Dalal and Triggs. |
| Dec 3, 2008 | Tea Talk | Alex Krizhevsky: An efficient parallel algorithm for Contrastive Divergence.
|
| Nov 26, 2008 | Tea Talk | Graham Taylor: Chapter 6 of Probabilistic Models for Music, Jean-Francois Paiement, PhD thesis |
| Sep 1, 2008 | Tea Talk | Past Tea Talks |
The Machine Learning seminar series is graciously sponsored by Yahoo!.