Machine Learning Meetings and Events

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Seminars: Seminars are held on Thursdays from 11am to Noon (talk starts 11:10am) in D.L. Pratt 290C unless otherwise noted. Seminars are coordinated by Kevin Swersky.

Cookies Talks: Cookies talks are held every WEDNESDAY at 4:00pm in D.L. Pratt 290C. Talks should be simple, accessible, and not exceed 15 minutes. Speakers bring snacks, and provide a copy of the presented paper.

Tutorials: Tutorials are held on Fridays from noon to 1pm in D.L. Pratt 290C. Tutorials are coordinated by Chris Maddison.

Talk slides can be found here.

Meeting Schedule:

Meeting Type: Dates:

Apr 8, 2014 Group Meeting Brian Kulis: Small-Variance Asymptotics for Large-Scale Learning
Apr 4, 2014 Group Meeting Mario Christoudias: Non-Linear Domain Adaptation with Boosting
Mar 25, 2014 Group Meeting Yoshua Bengio (Montreal): Unsupervised Deep Learning
Mar 20, 2014 Group Meeting Elad Mezuman: Globally Optimizing Graph Partitioning Problems Using Message Passing
Mar 17, 2014 Group Meeting Elad Mezuman: Globally Optimizing Graph Partitioning Problems Using Message Passing
Feb 20, 2014 Group Meeting Alexander G. Schwing (ETHZ): Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm
Feb 14, 2014 Group Meeting Jyri Juhani Kivinen: Statistical Models for Natural Scene Data
Feb 13, 2014 Group Meeting Srini Turaga: Using ConvNets, MALIS and crowd-sourcing to map the retinal connectome
Jan 23, 2014 Group Meeting Ryan Kiros: Multimodal Neural Language Models
Jan 9, 2014 Group Meeting David Duvenaud: Automatic Model-building with Gaussian processes
Nov 28, 2013 Group Meeting Jonathan Yedidia: The "Boundary Graph" Supervised Learning Algorithm for Regression and Classification
Nov 21, 2013 Group Meeting Nebojsa Jojic: Capturing and visualizing high order statistics with counting grids: Images, viruses and text
Nov 18, 2013 Group Meeting Michael Mozer: Using machine learning to amplify human learning
Nov 12, 2013 Group Meeting Richard Zemel: Anti-Discriminant Analysis
Oct 17, 2013 Group Meeting Mohammad Norouzi: Cartesian k-means
Oct 10, 2013 Group Meeting Chris Maddison: Annealing Between Distributions by Averaging Moments
Sep 26, 2013 Group Meeting Masashi Sugiyama: Machine Learning with Density Ratio Estimation
Sep 19, 2013 Group Meeting Kevin Swersky: Multi-Task Bayesian Optimization
Jul 4, 2013 Group Meeting Amos Storkey: Machine Learning Markets
Jun 13, 2013 Group Meeting Alex Graves: Do Androids Dream Of Electric Sheep: Generating Sequences with Recurrent Neural Networks
Jun 10, 2013 Group Meeting Abdel-rahman Mohamed: Deep convolutional neural networks for acoustic modeling
Apr 11, 2013 Group Meeting Yujia Li: Exploring Compositional High Order Pattern Potentials for Structured Output Learning
Mar 14, 2013 Group Meeting Roger Grosse (MIT): Model Selection in Large Compositional Spaces
Mar 7, 2013 Group Meeting Jimmy Ba: Standout: Adaptive Dropout on Feature Learning
Feb 28, 2013 Group Meeting Alexander G. Schwing (ETHZ): Efficient Inference and Learning for Structured Models
Feb 21, 2013 Group Meeting Kevin Swersky: Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning
Feb 7, 2013 Group Meeting Jimmy Ba: Standout: Adaptive Dropout on Feature Learning
Jan 24, 2013 Group Meeting Charlie Tang: Tensor Analyzers
Dec 12, 2012 Group Meeting Pierre Baldi (UCI): Deep Architectures and Deep Learning: Theory, Algorithms, and Applications
Nov 29, 2012 Group Meeting Anna Goldenberg: Using Machine Learning to Address Heterogeneity in Complex Human Diseases
Nov 22, 2012 Group Meeting Yisong Yue (CMU): Optimizing Recommender Systems as a Submodular Bandits Problem
Nov 15, 2012 Group Meeting Nitish Srivastava: Multimodal Learning with Deep Boltzmann Machines
Nov 8, 2012 Group Meeting George Dahl: How we won the Merck Molecular Activity Challenge
Nov 1, 2012 Group Meeting Lloyd Elliott (Gatsby): Dynamic clustering of genetic data with fragmentation-coagulation processes
Oct 25, 2012 Group Meeting Alex Krizhevsky: ImageNet classification with deep convolutional neural networks
Oct 10, 2012 Group Meeting Yoshua Bengio (Montreal): Regularized Auto-Encoders and MCMC
Oct 4, 2012 Group Meeting Roman Garnett (CMU): Bayesian Optimal Search and Surveying
Sep 27, 2012 Group Meeting Ilya Sutskever: The importance of initialization and momentum in deep learning.
May 31, 2012 Group Meeting Tapani Raiko ((Aalto University)): Deep Learning Made Easier by Linear Transformations in Perceptrons
May 28, 2012 Group Meeting Avrim Blum (CMU): Active (and Passive) Property Testing
May 24, 2012 Group Meeting Tyler Lu: Optimal Social Choice Functions: A Utilitarian View
May 7, 2012 Group Meeting Hal Daume III (Maryland): Complex Predictions need not be Slow
May 3, 2012 Group Meeting Laurent Charlin: Active Learning for Matching Problems
Apr 26, 2012 Group Meeting Volodymyr Mnih: Learning to Label Aerial Images from Noisy Data
Apr 25, 2012 Tea Talk Hannes Bretschneider:
Apr 20, 2012 Group Meeting Michael Jordan (Berkeley): Three short talks by Mike Jordan
Apr 18, 2012 Tea Talk Maksims Volkovs:
Apr 16, 2012 Group Meeting Tamir Hazan (TTI-C): The Partition Function, Random Maximum A-Posteriori Perturbations, and Approximate Inference
Apr 11, 2012 Tea Talk Nitish Srivastava:
Apr 9, 2012 Group Meeting Chris Williams (Edinburgh): Modelling of visual textures and object parts
Apr 5, 2012 Group Meeting Yee Whye Teh (Gatsby): TBD
Apr 4, 2012 Tea Talk Jasper Snoek:
Mar 29, 2012 Group Meeting Brendan Frey: Synaptic plasticity and alternative splicing
Mar 28, 2012 Tea Talk George Dahl:
Mar 21, 2012 Tea Talk Alex Krizhevsky:
Mar 15, 2012 Group Meeting Nitish Srivastava: Multimodal Learning with Deep Belief Nets
Mar 14, 2012 Tea Talk Kevin Swersky:
Mar 8, 2012 Group Meeting Maksims Volkovs: Loss-sensitive Training of Probabilistic Conditional Random Fields
Mar 7, 2012 Tea Talk Abdel-rahman Mohamed:
Mar 1, 2012 Group Meeting Charlie Tang: Robust Boltzmann Machines for Recognition and Denoising
Feb 29, 2012 Tea Talk Tijmen Tieleman:
Feb 16, 2012 Group Meeting Hannes Bretschneider: Visualizing Neural Networks with t-SNE
Feb 15, 2012 Tea Talk Nikola Karamanov:
Feb 9, 2012 Group Meeting Alex Graves: Sequence Transduction with Recurrent Neural Networks
Feb 8, 2012 Tea Talk Clement Chung:
Feb 2, 2012 Group Meeting Jasper Snoek: Opportunity Cost in Bayesian Optimization
Feb 1, 2012 Tea Talk Michael Leung: Online AUC Maximization
Jan 26, 2012 Group Meeting Sanja Fidler: Learning a Hierarchical Compositional Shape Vocabulary for Multi-class Object Representation
Jan 25, 2012 Tea Talk Lei Jimmy Ba: The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning
Jan 19, 2012 Group Meeting Danny Tarlow: Learning Probabilistic High-Order Message Passing Machines
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 8, 2011 Group Meeting Tijmen Tieleman: Autoencoders with hard-coded domain-specific decoders
Dec 6, 2011 Tea Talk James Martens: Quasi-Newton Markov chain Monte Carlo
Dec 1, 2011 Group Meeting Boyko Kakaradov: CANCELLED
Nov 29, 2011 Tea Talk Yujia Li: Learning Multiple Tasks using Manifold Regularization
Nov 24, 2011 Group Meeting Tomáš Mikolov (Brno Univ. of Tech.): Language modeling with recurrent neural networks
Nov 22, 2011 Tea Talk Boyko Kakaradov: Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees
Nov 16, 2011 Group Meeting Yutian Chen (UCI): Efficient Sampling with Kernel Herding
Nov 15, 2011 Tea Talk Laurent Charlin: Active Learning with Feedback on Both Features and Instances
Nov 10, 2011 Group Meeting George Dahl: Training Restricted Boltzmann Machines on Word Observations
Nov 9, 2011 Group Meeting Michael Wu (Lithium): Metrics -> Features -> Models -> Insights -> ROI
Nov 8, 2011 Tea Talk Volodymyr Mnih: Efficient Learning of Sparse, Distributed, Convolutional Feature Representations for Object Recognition
Nov 3, 2011 Group Meeting Graham Taylor (NYU): Learning Invariance through Imitation
Nov 1, 2011 Tea Talk Cecilia Chen Liu: Cascade Object Detection with Deformable Part Models
Oct 27, 2011 Group Meeting Kevin Swersky: On Autoencoders and Score Matching for Latent Energy-Based Models
Oct 25, 2011 Tea Talk Navdeep Jaitly: Using DBNs for speech recognition at Google
Oct 20, 2011 Group Meeting Jeroen Chua: Factorizing Color and Shape Using Hierarchical Palettes
Oct 13, 2011 Group Meeting Ilya Sutskever: Small minibatch Hessian-Free optimization and the Extended Gauss-Newton matrix.
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 26, 2011 Group Meeting Andrew Delong (UWO): Minimizing Energies with Hierarchical Costs
Sep 19, 2011 Tea Talk Danny Tarlow: Perturb-and-MAP Random Fields: Using Discrete Optimization to Learn and Sample from Energy Models,
Sep 19, 2011 Group Meeting Alexandros Panagopoulos (Stony Brook): Illumination Estimation Using Graphical Models
Aug 1, 2011 Group Meeting Vladimir Kolmogorov (UCL): Two topics in MAP-MRF inference
Jun 27, 2011 Group Meeting Babak Alipanahi (Waterloo): Multiclass modelling of asthmatic genotype-phenotype interactions
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 13, 2011 Group Meeting Danny Tarlow: Two Short Talks on Dynamic Message Passing Schedules for MAP Inference
Jun 8, 2011 Tea Talk Alex Shestopaloff: A quasi-Monte Carlo Metropolis algorithm
Jun 6, 2011 Group Meeting Nikola Karamanov: HOP-Depth-MAP: Joint inference of labels and depth using high order potentials.
May 25, 2011 Tea Talk Charlie Tang: The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization
May 25, 2011 Group Meeting Brian Potetz (Kansas): Applications of Efficient Statistical Inference over Continuous Higher-Order Distributions
May 18, 2011 Tea Talk Patrick Li: One-class SVM for Learning in Image Retrieval
May 16, 2011 Group Meeting Quaid Morris: Helping to cure cancer using topic models.
May 9, 2011 Group Meeting Yoshua Bengio (Montreal): Progress in Deep Learning at U. Montreal
May 4, 2011 Tea Talk Marc'Aurelio Ranzato: Non-local sparse models for image restoration
May 2, 2011 Group Meeting Mohammad Norouzi: Minimum Loss Hashing for Learning Compact Binary Codes
Apr 27, 2011 Tea Talk No Cookies Talk:
Apr 20, 2011 Tea Talk Tijmen Tieleman: Learning to Parse Images
Apr 18, 2011 Group Meeting Tyler Lu: Learning Mallows Models with Pairwise Preferences
Apr 13, 2011 Tea Talk Jeroen Chua: Object recognition with hierarchical stel models
Apr 11, 2011 Group Meeting Tara Sainath (IBM): Exemplar-Based Sparse Representations for Speech Recognition
Apr 6, 2011 Tea Talk Hugo Larochelle: SampleRank: Learning Preferences from Atomic Gradients
Apr 4, 2011 Group Meeting Douglas Tweed (Dept. of Physiology): Algorithms for near-optimal control
Mar 30, 2011 Tea Talk Leo Lee: Analysis and design of RNA sequencing experiments for identifying isoform regulation
Mar 28, 2011 Group Meeting Hugo Larochelle: The Neural Autoregressive Distribution Estimator
Mar 23, 2011 Tea Talk Inmar Givoni: How Kinect works
Mar 21, 2011 Group Meeting Kari Hoffman (York): Active exploration and the brain: how eye movements influence the neural code for faces and objects.
Mar 16, 2011 Tea Talk No cookies talk:
Mar 14, 2011 Group Meeting Volodymyr Mnih: Conditional Restricted Boltzmann Machines for Structured Prediction
Mar 9, 2011 Tea Talk Danny Tarlow: Learning programs: a hierarchical Bayesian approach.Learning programs: a hierarchical Bayesian approach.
Mar 7, 2011 Group Meeting Navdeep Jaitly: Learning alternative representations of speech signals
Mar 2, 2011 Tea Talk Maksims Volkovs: Fast approximation of the permanent for very dense problems
Feb 28, 2011 Group Meeting Laurent Charlin: Learning to improve matching
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 14, 2011 Group Meeting Jasper Snoek: Semiparametric Latent Variable Models for Guided Representation
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 24, 2011 Group Meeting Geoffrey Hinton: How to force unsupervised learning to discover the right representation of images
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 29, 2010 Group Meeting Hugo Larochelle: Learning to combine foveal glimpses with a third-order Boltzmann machine
Nov 24, 2010 Tea Talk Boyko Kakaradov: Robust Principal Component Analysis?
Nov 22, 2010 Group Meeting Inmar Givoni: Learning Better Image Representations Using ‘Flobject Analysis’
Nov 17, 2010 Tea Talk Ilya Sutskever: Maximin affinity learning of image segmentation
Nov 15, 2010 Group Meeting Radford Neal: MCMC Using Ensembles of States with Application to Gaussian Process Regression
Nov 8, 2010 Group Meeting Maksims Volkovs: Learning to Rank with Multiple Objectives
Nov 3, 2010 Tea Talk George Dahl: "Word representations: A simple and general method for semi-supervised learning"
Nov 1, 2010 Group Meeting Paolo Viappiani: Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets
Oct 27, 2010 Tea Talk Inmar Givoni: Norm-Product Belief Propagation : Primal-Dual Message Passing for Approximate Inference
Oct 25, 2010 Group Meeting Danny Tarlow: Learning with High Order Models and High Order Loss Functions
Oct 20, 2010 Tea Talk Ulrik Beierholm: Bayes-Optimal Human Decisions in a Reinforcement Learning Task
Oct 18, 2010 Group Meeting Peter O'Donovan: Learning Color Compatibility
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
Oct 4, 2010 Group Meeting Renqiang Min: Deep supervised non-linear embedding for classification and data visualization
Sep 29, 2010 Tea Talk Makims Volkovs: LambdaMART
Sep 27, 2010 Group Meeting Ilya Sutskever: A Recurrent Neural Network Language Model.
Sep 22, 2010 Tea Talk Laurent Charlin: A fast natural Newton method
Sep 20, 2010 Group Meeting Ryan Prescott Adams: Tree-Structured Stick Breaking for Hierarchical Data
Sep 15, 2010 Tea Talk Patrick Li: Convex Clustering
Sep 13, 2010 Group Meeting Marc'Aurelio Ranzato: How to make MRF's generate realistic samples of large resolution natural images
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 7, 2010 Group Meeting Quaid Morris: *CANCELLED* Using topic models to help cure cancer
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 17, 2010 Group Meeting Roland Memisevic: How to train a mixture of classifiers. in PT266
May 12, 2010 Tea Talk Amit Gruber: Nonparametric Latent Feature Models for Link Prediction
May 5, 2010 Tea Talk Patrick Li: Finding Scientific Topics
May 3, 2010 Group Meeting Wayne Hayes (UCI): Dynamical Grammars for Galaxy Image Recognition. in PT266
Apr 28, 2010 Tea Talk Inmar Givoni: Image Segmentation with A Bounding Box Prior
Apr 26, 2010 Group Meeting Hui Xiong: Bayesian learning reveals the splicing code
Apr 21, 2010 Tea Talk Vinod Nair: Attribute and Simile Classifiers for Face Verification
Apr 19, 2010 Group Meeting George Dahl: Phone Recognition with mcRBM feature extraction and DBNs
Apr 14, 2010 Tea Talk Marc'Aurelio Ranzato: The Role of Features, Algorithms and Data in Visual Recognition
Apr 12, 2010 Group Meeting Ryan Prescott Adams: Dependent Probabilistic Matrix Factorization
Apr 7, 2010 Tea Talk Maks Volkovs: Expected Reciprocal Rank for Graded Relevance
Apr 5, 2010 Group Meeting Tyler Lu: Consensus decision making, and its interplay with preference learning and collaborative filtering
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 22, 2010 Group Meeting Alex Krizhevsky: Image Retrieval using Short Binary Codes found by Deep Learning
Mar 17, 2010 Tea Talk George Dahl: Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions
Mar 15, 2010 Group Meeting Marc'Aurelio Ranzato: Modeling natural images with higher-order Boltzmann Machines
Mar 10, 2010 Tea Talk Clement Chung: Clustering Sequence Sets for Motif Discovery
Mar 8, 2010 Group Meeting Ilya Sutskever: On the convergence properties of Contrastive Divergence
Mar 1, 2010 Group Meeting Richard Zemel: Learning to label images with latent topic random fields
Feb 24, 2010 Tea Talk Nikola Karamanov: "Statistical correlations between two-dimensional images and three-dimensional structures in natural scenes"
Feb 22, 2010 Group Meeting Maksims Volkovs: Learning to Maximize Expected Ranking Gain
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
Feb 8, 2010 Group Meeting Charlie Tang: Sparsely Connected Deep Networks for More Robust Visual Recognition
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 25, 2010 Group Meeting Brendan Frey: Learning the genetic code governing neural-specific messages
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.
Jan 18, 2010 Group Meeting Volodymyr Mnih: Learning to Detect Roads in High-Resolution Aerial Images
Jan 11, 2010 Group Meeting James Martens: Deep Learning via Hessian-free Optimization
Jan 6, 2010 Group Meeting Ilya Sutskever: Unsupervised Semantic Parsing, by Hoifung Poon and Pedro Domingos
Jan 4, 2010 Group Meeting Michael Black: An Additive Latent Feature Model for Transparent Object Recognition
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 30, 2009 Group Meeting Vangelis Kalogerakis: Data-driven part recognition of 3D meshes
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 23, 2009 Group Meeting Amit Gruber: Latent Topic Models for Hypertext
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 16, 2009 Group Meeting Yoshua Bengio (Montreal): Experimental Investigations into Deep Architectures. in PT266
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 9, 2009 Group Meeting Inmar Givoni: Hierarchical Affinity Propagation
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).
Nov 2, 2009 Group Meeting Pascal Poupart (Waterloo): Reinforcement Learning: A Model-Based Bayesian Approach. in PT266
Oct 28, 2009 Tea Talk Danny Tarlow: Joint optimization of segmentation and appearance models Sara Vicente, Vladimir Komogorov, Carsten Rother
Oct 26, 2009 Group Meeting Nevena Lazic: Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms
Oct 21, 2009 Tea Talk Ben Marlin: Max Margin Restricted Boltzmann Machines.
Oct 19, 2009 Group Meeting Iain Murray: Elliptical Slice Sampling
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
Oct 8, 2009 Group Meeting Yee Whye Teh: Nonparametric Bayesian models tutorial (2).
Oct 7, 2009 Group Meeting Yee Whye Teh: Nonparametric Bayesian models tutorial (1).
Oct 5, 2009 Group Meeting Kevin Regan: Regret Based Reward Elicitation for Markov Decision Problems
Sep 28, 2009 Group Meeting Danny Tarlow: Max Product in High Order Factor Graphs
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 21, 2009 Group Meeting Ryan Prescott Adams: Infinite Belief Networks
Sep 16, 2009 Tea Talk Jasper Snoek: Healing the Relevance Vector Machine through Augmentation, by Carl Rasmussen and Joaquin Quinonero-Candela
Sep 14, 2009 Group Meeting Ilya Sutskever: Modelling Relational Data using Bayesian Clustered Tensor Factorization. in PT266
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
May 6, 2009 Group Meeting Aapo Hyvärinen: Separating sources and analyzing causality in brain waves. Wed 4pm in PT266
May 4, 2009 Group Meeting Tom Mitchell: Read the Web: Toward Never-Ending Language Learning. in PT266
Apr 29, 2009 Tea Talk Ilya Sutskever: Linear spatial pyramid matching using sparse coding for image classification by Yang, Yu, Gong, and Huang
Apr 27, 2009 Group Meeting Jim Huang: Cumulative distribution networks: Graphical models for cumulative distribution functions
Apr 22, 2009 Tea Talk Maks Volkvos: COFIRANK - Maximum Margin Matrix Factorization for Collaborative Ranking
Apr 20, 2009 Group Meeting Seunghak Lee: Non-metric Neighbor Embedding
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 6, 2009 Group Meeting Laurens van der Maaten (TiCC/Tilburg): On Non-Metric and Parametric Variants of t-SNE
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.
Mar 2, 2009 Group Meeting James Bergstra (Montreal): Machine Learning for Music Genre Classification
Feb 25, 2009 Tea Talk Eddie Ng: Most Likely Heteroscedastic Gaussian Process Regression By Kersting, Plagemann, Pfaff, and Burgard.
Feb 23, 2009 Group Meeting Timothy P. Lillicrap (Queen's) and Stephen H. Scott: How do the properties of the musculoskeletal system shape neural activity in primary motor cortex?. in PT266
Feb 11, 2009 Tea Talk Andriy Mnih: Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression., by David Mimno and Andrew McCallum
Feb 9, 2009 Group Meeting Hugo Larochelle: To recognize shapes, first learn to generate reconstruct images. in PT266
Feb 4, 2009 Tea Talk Ruslan Salakhutdinov: Fixing max-product: Convergent message passing algorithms for MAP LP-relaxations, by Amir Globerson , Tommi Jaakkola
Feb 2, 2009 Group Meeting Marc'Aurelio Ranzato (NYU): Unsupervised Learning of Feature Hierarchies
Jan 28, 2009 Group Meeting Yann LeCun: Learning Hierarchies of Invariant Visual Features.
Jan 28, 2009 Group Meeting Yann LeCun (NYU): Learning Hierarchies of Invariant Visual Features.. Wed 4pm
Jan 21, 2009 Tea Talk David Warde-Farley: Efficient Inference in Phylogenetic InDel Trees by Bouchard-Cote, Jordan, and Klein.
Jan 19, 2009 Group Meeting Ilya Sutskever: Using matrices to model symbolic relationship
Jan 14, 2009 Tea Talk Jasper Snoek: Histograms of Oriented Gradients for Human Detection by Dalal and Triggs.
Jan 12, 2009 Group Meeting William Ryu: Dimensionality and Dynamics in the Behavior of C. elegans
Dec 3, 2008 Tea Talk Alex Krizhevsky: An efficient parallel algorithm for Contrastive Divergence.
Dec 1, 2008 Group Meeting Yoseph Barash: Inferring RNA Regulatory Codes that Predict Tissue-Dependent Alternative Splicing
Nov 26, 2008 Tea Talk Graham Taylor: Chapter 6 of Probabilistic Models for Music, Jean-Francois Paiement, PhD thesis
Nov 24, 2008 Group Meeting Yoseph Barash: TBA
Nov 24, 2008 Group Meeting Vinod Nair: Deep Belief Nets for Visual Object Recognition: Part II
Nov 17, 2008 Group Meeting Dustin Lang: Measuring the undetectable
Nov 10, 2008 Group Meeting Katherine Heller (Cambridge): Bayesian Hierarchical Clustering
Nov 3, 2008 Group Meeting Graham Taylor: Deep componential models for human motion
Oct 27, 2008 Group Meeting Andriy Mnih: A Scalable Hierarchical Distributed Language Model
Oct 20, 2008 Group Meeting Eric Hsu: Solving Satisfiability (SAT) Problems Using Loopy Belief Propagation, and Deriving a Convergent Variant Based on EM
Oct 6, 2008 Group Meeting Laurent Charlin: Hierarchical POMDP Controller Optimization by Likelihood Maximization
Oct 1, 2008 Group Meeting Vinod Nair: Deep Belief Nets for Visual Object Recognition. Wednesday 4pm
Sep 22, 2008 Group Meeting Geoffrey Hinton: Visualizing high-dimensional data using t-SNE
Sep 15, 2008 Group Meeting Ruslan Salakhutdinov: Learning Multilayer Boltzmann Machines
Sep 1, 2008 Group Meeting Past Group Meetings
Sep 1, 2008 Tea Talk Past Tea Talks
Aug 1, 2008 Special Event CIFAR NCAP Summer School 2008