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Every Wednesday at 4:00 PM in Pratt 290C the learning group meets for tea, cookies, and a short informal presentation by one of the group members at 4.15 PM.
There are three rules:
Should you have any problems with the schedule, please try to swap with someone, then contact Roland Memisevic.
June 6 - |
2008
Jan 16 - Roland Memisevic Switching to Python
23 - Inmar Givoni Linear Programming Analysis of Loopy Belief Propagation for Weighted Matching
30 - Mike Brudno Ab Initio Whole Genome Shotgun Assembly With Mated Short Reads
Feb 6 - Alex Krizhevsky Extreme Components Analysis
13 - Dustin Lang How to use the Google Maps browser to view your own data
27 - James Martens A deterministic approximation to the partition function in Boltzmann machines.
Mar 5 - Danny Tarlow A Nonparametric Bayesian Approach to Modeling Overlapping Clusters. (Heller, Ghahramani)
12 - Andriy Mnih Deterministic Latent Variable Models and Their Pitfalls (Welling, Chemudugunta, Sutter)
19 - Quaid Morris Predicting expression patterns from regulatory sequence in Drosophila segmentation
26 - Iain Murray Catching Up Faster in Bayesian Model Selection and Model Averaging (van Erven, Gruenwald, de Rooij)
Apr 2 - Vinod Nair Steerable Random Fields (Roth, Black)
16 - Rama Natarajan Validating Bayesian Models of Perception (Stocker, Simoncelli)
30 - Ruslan Salakhutdinov - Studies in lower bounding probability of evidence using the Markov inequality (Gogate, Bidyuk, Dechter)
May 14 - Ilya Sutskever The tempotron: a neuron that learns spike timing-based decisions (Gütig, Sompolinsky)
21 - Martin Renqiang Min More Efficiency in Multiple Kernel Learning (Rakotomamonjy, Bach, Canu, Grandvalet)
28 - Tijmen Tieleman Long Short-Term Memory (Hochreiter, Schmidhuber)
2007
Jan 10 - Ilya Sutskever A new class of upper bounds on the log partition function
17 - Rich Zemel How Behavioral Constraints May Determine Optimal Sensory Representations
24 - Vincent Cheung Locality-Sensitive Hashing Scheme Based on p-Stable Distributions
31 - Brendan Frey Possibly the second best clustering algorithm in the world
Feb 7 - Stephen Fung Estimating Intrinsic Component Images using Non-Linear Regression (Tappen, Adelson and Freeman)
14 - Inmar Givoni 'Beauty and the Machine', Digital Face Beautification
28 - Xuming He Dynamic Topic models
Mar 7 - Roland Memisevic Semi - supervised learning of parametric models
14 - Jim Huang Structured Priors for Structure Learning (Mansinghka, Kemp, Tenenbaum and Griffiths)
28 - Scott Leishman The "integral image" trick
Apr 18 - Ted Meeds An auxiliary variable method for sampling mixture distributions
25 - Eddie Ng Functional principal component analysis of financial time series (Ingrassia and Costanzo)
May 2 - Renqiang Min Large Margin Hidden Markov Models for Automatic Speech Recognition (Sha and Saul)
9 - Andriy Mnih A short introduction to observable operator models for stochastic processes (Jaeger)
16 - Vinod Nair What makes a good model of natural images? (Weiss and Freeman)
30 - David Ross Learning Module Networks (Pe'er, Regev, Koller, Friedman)
June 6 - Dustin Lang A point matching trick
13 - Rama Natarajan Predictive coding in the visual cortex (Rao and Ballard)
September 19 - Radford Neal Learning policies with external memory (Peshkin, Meuleau, Kaelbling)
26 - Ruslan Salakhutdinov Simulating Ratios of Normalizing Constants via a Simple Identity: A Theoretical Exploration (Meng and Wong)
October 3 - Ofer Shai Splitting and Merging Components of a Nonconjugate Dirichlet Process Mixture Model" (Neal and Jain)
10 - Ilya Sutskever Relative Loss Bounds for Single Neurons (Helmbold, Kivinen, Warmuth)
17 - Danny Tarlow Variational methods for the Dirichlet process (Blei and Jordan)
24 - Graham Taylor Rate- and phase-coded autoassociative memory. (Lengyel and Dayan)
31 - Tijmen Tieleman Discriminative Learning for Differing Training and Test Distributions (Bickel, Brueckner, Scheffer)
November 7 - Rich Zemel Scene Completion Using Millions of Photographs (Hays and Efros)
14 - Vincent Cheung Optimized Color Sampling for Robust Matting (Wang and Cohen),
Soft Scissors: An Interactive Tool for Realtime High Quality Matting (Wang, Agrawala, Cohen)
21 - Brendan Frey "The vertex substitution heuristic and how Quaid nearly won the $5000 affinity propagation prize"
28 - Eddie Ng Everything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask (Genest and Favre)
2006
Jan 10 - Liam Stewart A Graphical Model for Chord Progressions Embedded in a Psychoacoustic Space (Paiement et al)
18 - Rich Zemel Predictive Linear-Gaussian Models of Stochastic Dynamical Systems (Rudary et al)
24 - Vinod Nair Multilinear Independent Component Analysis (Vasilescu & Terzopoulos)
Feb 1 - Xuming He Learning Hierarchical Models of Scenes, Objects, and Parts (Sudderth et al)
8 - Geoff Hinton
15 - Renqiang Min
22 - Ben Marlin An Application of Markov Random Fields to Range Sensing (Diebel & Thrun)
Mar 1 - Andriy Mnih Discriminative Models, Not Discriminative Training (Minka)
15 - Nati Srebro Sparse Distributed Memory (Kanerva)
22 - Jim Huang
29 - Delbert Dueck
April 5 - Radford Neal
12 - Dustin Lang
19 - Jennifer Listgarten Multiple Interval Mapping for Quantitative Trait Loci (Kaoa et al)
25 - Tijmen Tieleman Integrating Topics and Syntax (Griffiths et al)
May 3 - Scott Leishman Keyboard Acoustic Emanations Revisited (Zhuang et al)
10 - Quaid Morris (Morris & Ray)
17 - David Ross An empirical study of the naive Bayes classifier (Rish)
24 - Sam Roweis
31 - Simon Osindero A Closed Form Solution To Natural Image Matting (Levin et al)
June 7 - Ruslan Salakhutdinov Nonparametric empirical Bayes for the Dirichlet process mixture model (McAuliffe et al)
21 - Scott Sanner Online Feature Discovery in Relational Reinforcement Learning
28 - Ted Meeds Direct Clustering of a Data Matrix (Hartigan)
Jul 5 - Graham Taylor Practical parameterization of rotations using the exponential map (Grassia)
19 - Babak Shahbaba Integrating multi-attribute similarity networks for robust representation of the protein space (Camoglu et al)
26 - Ofer Shai Fast Approximate Energy Minimization via Graph Cuts (Boykov et al)
Aug 2 - Ilya Sutskever Apprenticeship learning via inverse reinforcement learning (Abbeel and Ng)
23 - Xuming He Multiple Instance Boosting for Object Detection (Viola et al)
30 - Andriy Mnih
Sept 13 - Roland Memisevic Some nonlinear extensions of conditional random fields
20 - Geoff HintonBiologically Plausible Error-driven Learning using Local Activation Differences: The Generalized Recirculation Algorithm
27 - Renqiang Min Profile-based String Kernels for Remote Homology Detection and Motif Extraction.
Oct 4 - Sam Roweis $ How to make a Million Dollars $
11 - Rama NatarajanEquivalence of Backpropagation and Contrastive Hebbian Learning in a Layered Network
18 - Radford Neal Statistics / machine learning for high energy physics applications
25 - Eddie Ng A non-local algorithm for image denoising
Nov 1 - David Ross Parallel programming with MatlabMPI
8 - Vinod Nair Improving Wavelet Image Compression with Neural Networks
15 - Ruslan Salakhutdinov Frequentist vs. Bayesian ways of performing estimation and hypothesis testing
22 - Ofer Shai Greedy Layer-Wise Training of Deep Networks
29 - Tijmen Tieleman Hierarchical Statistical Learning of Generic Parts of Object Structure.
Dec 13 - Danny Tarlow Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing
20 - Graham Taylor Efficient Learning of Sparse Representations with an Energy-Based Model
2005
Jan 12 - Jianguo Zhang Semi-Supervised Learning of Mixture Models (Cozman et al)
19 - Anitha Kannan Separating Reflections from a Single Image Using Local Features (Levin, Zomet & Weiss)
26 - Quaid Morris RankMotif:Finding Motifs Using Gene Rankings
Feb 2 - Kevin Laven Learning To Segment A Page Image
9 - Ted Meeds Breaking SVM Complexity With Cross-Training (Bakur, Bottou & Weston)
16 - Rolan Memisevic Kernel Dependency Estimation (Weston et al.)
23 - Andriy Mnih Maximum Likelihood Estimation of Intrinsic Dimension (Levina & Bickel)
Mar 2 - Rama Natarajan A Temporal Kernel-Based Model for Tracking Hand-Movements from Neural Activities (Shpigelman et al)
9 - David Ross Matching words and pictures (Barnard et al). Also more background here
16 - Radford Neal Getting it Right: Joint distribution test of posterior simulatorss (Geweke)
23 - Simon Osindero Non-negative Matrix Factorization with Sparseness Constraints (Hoyer)
30 - Simon Osindero Mining Associated Text and Images with Dual-Wing Harmoniums (Xing et al)
Apr 6 - Graham Taylor Colorization using Optimization (Levin et al)
13 - Vinod Nair Maximum Margin Clustering (Xu et al)
20 - Babak Shahbaba Dependent Gaussian Processes (Boyle & Frean)
27 - Ofer Shai Physical Network Models and Multi-source Data Integration (Yeang & Jaakola)
May 18 - Ilya Sutskever Recursive Algorithms for Approximating Probabilities in Graphical Models (Jaakola & Jordan)
25 - Liam Stewart Collective Segmentation and Labeling of Distant Entities in Information Extraction (Sutton & McCallum)
Jun 8 - Kejie Bao Improved Fast Gauss Transform and Efficient Kernel Density Estimation (Yang et al)
15 - Kannan Achan Efficient belief propagation for early vision (Felzenszwalb & Huttenlocher)
22 - Xuming He Mid-level Cues Improve Boundary Detection (Ren et al)
29 - Rich Zemel Population coding of shape in area V4 (Pasupathy & Connor)
Jul 6 - Renqiang Min Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning (Zhu et al)
20 - Ben Marlin Near-Optimal Nonmyopic Value of Information in Graphical Models (Krause & Guestrin)
27 - Jim Huang A direct formulation for sparse PCA using semidefinite programming (d'Aspremont et al)
Aug 3 - Quaid Morris Using the triangle inequality to accelerate k-means (Elkan)
17 - Nati Srebro Highlights From ICML 2005
24 - Andriy Mnih Learning Coordination Classifiers (Guo et al)
31 - Radford Neal Short-cut Metropolis Method (Neal)
Sep 7 - David Ross Dynamical Systems Trees (Howard & Jebara)
14 - Sam Roweis Distance Metric Learning for Large Margin Nearest Neighbor Classification (Weinberger et al)
21 - Ruslan Salakhutdinov On the Slow Convergence of EM and VBEM in Low-Noise Linear Models (Peterson et al)
28 - Simon Osindero Estimation of Non-Normalized Statistical Models by Score Matching (Hyvarinen)
Oct 5 - Rama Natarajan Intrinsically Motivated Reinforcement Learning (Singh et al)
12 - Ofer Shai Q-clustering (Narasimhan et al)
19 - Roland Memisevic Adapting SMO to Train Multinomial Logistic Regression Models
26 - Ted Meeds A Probabilistic Model for Binary Matrix Factorisation
Nov 16 - Babak Shahbaba Improving classification when a class hierarchy is available using a hierarchy-based prior (Shahbaba & Neal)
30 - Graham Taylor Clustering by Compression (Cilibrasi & Vitanyi)
Dec 14 - Ilya Sutskever Cost-Sensitive Learning by Cost-Proportionate Example Weighting (Zadrozny et al)
2004
Jan 14 - Matthew Beal Gaussian Processes in Reinforcement Learning (Rasmussen, Kuss)
21 - Shamim Ahmed Two Algorithms for Nearest Neighbor Search in High Dimensions (Kleinberg)
28 - Kejie Bao Online EM (Bao)
Feb 4 - Kannan Achan Probabilistic Inference of Speech Signals from Phaseless Spectrograms (Achan, Roweis, Frey)
11 - Miguel Carreira-Perpinan Optimal Manifold Representation of Data: An Information Theoretic Approach (Chigirev, Bialek)
25 - Jacob Goldberger An efficient similarity measure based on approximations of KL-divergence between two Gaussian mixtures (Goldberger, Greenspan, Gordon)
Mar 17 - Xuming He Feature Extraction by non-parametric mutual information maximization (Torkkola)
24 - Geoff Hinton (to appear)
31 - Anitha Kannan A Generalized Mean Field Algorithm for Variational Inference in Exponential Families (Xing, Jordan, Russell)
Apr 7 - Krunoslav Kovac email Krunoslav for the ppt slides
14 - Ben Marlin On an Equivalence between PLSI and LDA (Girolami, Kaban)
21 - Jennifer Listgarten Explicitly Representing Expected Cost: An Alternative to ROC Representation (Drummond, Holte)
28 - Quaid Morris Predicting Gene Expression from Sequence (Beer, Tavazoie)
May 5 - Kevin Adam Laven Segmentation and Classification of Scanned Academic Journals (Roweis, Leishman, Laven) .sxi is Star Office presentation format.
12 - Ted Meeds Random walks and an O*(n5) volume algorithm for convex bodies (Kannan, Lovász, Simonovits), Ted's slides pdf
19 - Roland Memisevic Limitations of nonlinear PCA as performed with generic neural networks (Malthouse)
26 - Renqiang Min A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning (Mřller)
June 9 - Andriy Mnih (to appear)
16 - Mustansir Mukhles (to appear)
23 - Rama Natarajan Banburismus and the Brain: Decoding the Relationship between Sensory Stimuli, Decisions, and Reward (Gold, Shadlen)
30 - Radford Neal An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants (Moller, Pettitt, Berthelsen, Reeve)
July 7 - David Ross Toward Optimal Active Learning through Sampling Estimation of Error Reduction (Roy, McCallum)
14 - Simon Osindero An overview of the Swendsen-Wang sampling method, applied to Boltzmann machines (Swendsen & Wang; Edwards & Sokal; Higdon)
21 - Sam Roweis Learning Associative Markov Networks (Taskar et al.), and an overview of other ICML 2004 highlights
28 - Ofer Shai Statistical significance for genome-wide studies. (Storey & Tibshirani)
Aug 4 - Miguel Carreira-Perpinan Geodesic Entropic Graphs for Dimension and Entropy Estimation in Manifold Learning (Costa & Hero)
11 - Nebojsa Jojic (INVITED TALK)
18 - Miles Trochesset Clustering Labeled Data and Cross-Validation for Classification with Few Positives in Yeast (Trochesset & Bonner)
25 - Khashayar Rohanimesh Training Conditional Random Fields via Gradient Tree Boosting (Dietterich et al.)
Sep 1 - Ilya Sutskever Haskell script for generating vectorised matlab expressions from 'quasi-matlab' code
8 - Liam Stewart Learning Low Dimensional Predictive Representations (Rosencratz, Gordon & Thrun)
22 - Rich Zemel Achieving robust neural representations: An account of repetition suppression (Work in progress)
29 - Kejie Bao Variational Learning and Bits-back Coding (Honkela & Valpola)
Oct 6 - Aaron Hertznan Learning Physics-Based Motion Style
20 - Nati Srebro On Kernels, Margins and Low-dimensional Mappings (Balcan,Blum & Vempala).
See also An elementary proof of the Johnson-Lindenstrauss Lemma and Limitations of learning via embeddings in euclidean half spaces
27 - Xuming He Contextual Models for Object Detection using Boosted Random Fields (Torralba,Murphy & Freeman)
Nov 10 - Geoff Hinton Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless telecoms Jaeger Et Al.
17 - Krunoslav Kovac An Auditory Paradigm for Brain--Computer Interfaces (Hill Et Al.)
2003
January
15 - Sam Roweis
22 - Yee Whye Teh
29 - Yee Whye special
February
5 - Ruslan Salakhutdinov
12 - Matt Beal
19 - Max Welling
26 - Quaid Morris
March
5 - David Ross (actually on 6th)
12 - Geoff
19 - Sam (Stolcke & Omohundro)
26 - Karolina
April
2 - Miguel
9 - Chris Harvey
16 - Xuming He
23 - Krunoslav
30 - Ben Marlin
May
7 - Renqiang Min
14 - Andriy Mnih
21 - Al-Mustansir Mukhles
28 - Nina Thiessen
June
4 - NIPS panic / DJCM Dasher Demo.
11 - Rich Zemel
18 - Radford N
25 - Jakob V
July
2 - Joaquin C
9 - no tea (Sam R skips)
16 - Max W (bound propagation)
23 - Sam R (skip lists)
30 - no tea (Chris Williams' talk)
August
6 - Xuming H
13 - Matt B
20 - Quaid M (missed for ICML)
27 - Rómer R
September
3 - Chris H
10 - Quaid M (replacing Miguel C-P)
17 - Geoff H
24 - Krunoslav K
October
1 - Invited speaker (Botond Szatmary)
8 - Ben M (replacing Renqiang M)
15 - Andriy M
22 - Al-Mustansir M
29 - Miguel C-P (replacing Russ S)
November
5 - Nina T
12 - Rich Z
19 - Yousuf S
26 - Brendan F
December
no talks this month.