Machine Learning and Friends Lunch

FALL 2006

Date Speaker Abstract Lab Institution

12/07 Hema Raghavan TBD CIIR UMASS

11/30 Gideon Mann TBD IESL UMASS

11/16 Pippin Wolfe TBD ALL UMASS

11/09 George Konidaris TBD ALL UMASS

11/02 Stephan Murtagh Predicting the Difficulty of Factored Multi-Agent Domains MLL UMASS

10/26 Charles Sutton Local Training and Belief Propagation IESL UMASS

10/19 John Fisher Information-driven Inference in Resource-constrained Envronments MIT

10/12 Marek Petrik Basis Construction for Value Function Approximation Using Laplacian and Krylov Methods Resource-Bounded
Reasoning Laboratory UMASS

Andrew Fast The NFL Coaching Network: Analysis of the Social Network Among Professional Football Coaches KDL UMASS

10/05 Fernando Diaz Pseudo-Aligned Multilingual Corpora CIIR UMASS

09/29 (Friday 1.30) Erik Sudderth Learning Object Appearance Models via Transformed Dirichlet Processes Laboratory for Information and Decision Systems &
Computer Science and Artificial Intelligence Laboratory MIT

09/28 Amit Singhal Challenges in Running a Commercial Search Engine Google

09/14 Pallika Kanani Resource-Bounded Information Gathering for Entity Resolution IESL UMASS

Ben Carterette Minimal Test Collections for Retrieval Evaluation (SIGIR 06 Best Paper) CIIR UMASS

SUMMER 2006

Date Speaker Abstract Lab Institution

05/11 Charles Elkan Modeling Word Burstiness Using the Dirichlet Distribution UCSD

SPRING 2006

Date Speaker Abstract Lab Institution

05/11 Wei Li Pachinko Allocation: DAG-Structured Mixture Models of Topic Correlations IESL UMASS

05/04 Matthew J. Rattigan Using Structure Indices for Efficient Approximation of Network Properties KDL UMASS

04/13 Don Metzler Beyond Bags of Words: A Markov Random Field Model for Information Retrieval CIIR UMASS

04/06 Sharon Goldwater Learning Linguistic Structure using Nonparametric Bayesian Techniques COG Brown

03/30 Jerod Weinman Leveraging Character Similarity to Improve Recognition of Novel Fonts VIS UMASS

03/30 Shaolei Feng A Hierarchical, HMM based Automatic Evaluation of OCR Accuracy for a Digital Library of Books MIR UMASS

03/16 Brendan Burns Reasoning about sensor uncertainty in probabilistic planning LPR UMASS

03/09 Ron Bekkerman Non-Bayesian Networks CIIR UMASS

03/02 Chris Pal Computer Vision and Machine Learning - Representations and Algorithms for Creating Interactive Visual Media IESL UMASS

02/23 Aron Culotta Integrating Probabilistic Extraction Models and Data Mining to Discover Relations and Patterns in Text IESL UMASS

02/16 Fernando Diaz Regularizing Ad Hoc Information Retrieval Scores CIIR UMASS

FALL 2005

Date Speaker Abstract Lab Institution

12/01 George Konidaris Agent Space vs. Problem Space: Knowledge and Skill Transfer in Reinforcement Learning ALL UMASS

11/17 Hal Daume III Learning in Search: Practical Learning Theory for Hard Language Problems NLG ISI

11/10 Khash Rohanimanesh Concurrent Decision Making in Markov Decision Processes ALL UMASS

11/03 Mauro Maggioni Diffusion Wavelets for multiscale analysis on manifolds and graphs: constructions and applications Applied
Mathematics Yale

10/27 Dima Lisin Using All Available Information: Combining Feature Vectors and Bags of Features for Object Class Recognition. VIS UMASS

10/20 Xuerui Wang Group and Topic Discovery from Relations and Their Attributes IESL UMASS

10/13 Wei Wei Identifying 802.11 Wireless Traffic from Passive Measurements Using Iterative Bayesian Inference CNRG UMass

10/06 Micheal Kelm Feature Extraction and Classification in Magnetic Resonance Spectroscopic Imaging Multidimensional
Image
Processing Univ. of Heidelberg

10/06 Victoria Manfredi Switching Kalman Filters for Prediction and Tracking in an AdaptiveMeteorological Sensing Network CNRG UMass

09/29 Andras Ferencz Building Classification Cascades for Visual Identification from One Example Computer
Vision
Group UC Berkeley

09/19 Matthew Taylor Behavior Transfer for Value-Function-Based Reinforcement Learning UT Austin

SPRING 2005

Date Speaker Abstract Lab Institution

05/12 Stephen Murtagh Solving Large Problem Domains with Goal Regression MLL UMass

05/05 Chris Pal Probability Models for Joint Row Column Clustering and High Dynamic Range Image Processing IESL UMass

04/28 Sridhar Mahadevan SAMUEL MEETS AMAREL: A Coordinate-Free Framework for Learning Behavior and Representation ALL UMass

04/14 David Parkes Optimal Coordinated Learning Among Self-Interested Agents in the Multi-Armed Bandit Problem EconCS Harvard

04/07 Ron Bekkerman Distributional Clustering and Graphical Models IESL UMass

04/07 Andrés Corrada-Emmanuel Optimal Number of Topics in LDA Models IESL UMass

03/31 Charles Sutton Cliquewise Training for Undirected Models IESL UMass

03/24 Steve Hart A Relational Representation for Procedural Task Knowledge LPR UMass

03/09 Martin C. Martin ... But What About The Structure? IcoSystem

03/03 Mike Ross Learning Static Object Segmentation from Motion Segmentation CSAIL MIT

02/24 Sam Roweis Neighbourhood Components Analysis Machine Learning University of Toronto

02/17 Roni Khardon Learning and Logic: Theoretical Foundations and Efficient Systems Dept. of Computer Science Tufts University

02/10 Ivon Arroyo Applications of machine learning to education: Inferring learning and attitudes from students' behavior in a tutoring system CKC UMass

FALL 2004

Date Speaker Abstract Lab Institution

12/09 CMPSCI 689 Machine Learning Class Projects UMass

12/02 Robert Platt Generalization and Differentiation of Robot Manipulation Skills LPR UMass

11/18 Özgür Şimşek Acquiring useful skills in reinforcement learning ALL UMass

11/4 TJ Brunette From Sequence to Structure: A Holistic Approach LPR UMass

10/28 Charles Sutton Learning in Markov Random Fields with Contrastive Free Energies IESL UMass

10/21 Hema Raghavan Interactive Feature Selection in Active Learning for Text Classification CIIR UMass

10/21 Gary Huang Document Classification via Multiple Linear SVM Projections IESL UMass

10/14 Ramesh Nallapati Generative Classification Models for Information Retrieval CIIR UMass

10/07 Alicia Wolfe Object Based Abstraction Using MDP Homomorphisms ALL UMass

09/30 Yee Whye Teh Hierarchical Dirichlet processes: A Bayesian approach to sharing clusters among related groups Dept. of Computer Science UC-Berkeley

09/23 Sarah Osentoski Learning Hierarchical models of activity ALL UMass

09/23 Jerod Weinman Sign Detection in Natural Images with Conditional Random Fields VIS UMass

09/16 Erik Learned-Miller Toward better face recognition: non-parametric maximum likelihood methods for separating causes in images VIS UMass

SUMMER 2004

Date Speaker Abstract Lab Institution

08/26 Ryan McDonald Conditional models for natural language dependency parsing Computer Science Dept. UPenn

07/22 Aron Culotta Extracting social networks and contact information from email and the Web IESL UMass

07/22 Toni Rath A search engine for historical manuscript images CIIR UMass

07/15 Brendan Burns Approximate Models, Utility and Robotic Motion Planning LPR UMass

06/24 Nir Friedman Probabilistic Models for Identifying Regulation Networks CMBL The Hebrew University of Jerusalem

SPRING 2004

Date Speaker Abstract Lab Institution

05/13 Natalia Hernandez Gardiol Planning with action equivalences AI Lab MIT

05/06 David Stracuzzi Learning Many Layers of Structure MLL UMass

04/29 Andrés Corrada-Emmanuel Variational Approximations for Inference over Graphical Models CIIR UMass

04/22 Sam Roweis Discrimination with Generative Models Machine Learning University of Toronto

04/15 Claudia Goldman-Shenhar Decentralized Language Learning Through Acting RBR UMass

04/08 David Blei Fast and Flexible Clustering---Variational methods for the Dirichlet process CS UC-Berkeley

04/08 Paul Utgoff Learning From Textbooks MLL UMass

04/01 Andrew Arnt Attribute Measurement Policies for Cost-effective Classification RBR UMass

03/25 Anders Jonsson A novel approach to abstraction discovery in MDPs ALL UMass

03/11 Ramesh Nallapati Discriminative models for Information Retrieval CIIR UMass

03/04 Robert Moll Machine Learning for Combinatorial Optimization TCSC UMass

02/26 Michael Rosenstein From Supervisory Control To Intelligent Prosthetics ALL UMass

02/19 Andrew Fagg Reaching and Grasping Skills LPR UMass

02/12 Charles Sutton Models for Labeling and Segmenting Sequence Data IESL UMass

FALL 2003

Date Speaker Abstract Lab Institution

12/11 CMPSCI 689 Machine Learning Class Projects UMass

11/20 Jeremy Pickens Polyphonic Music Modeling with Random Fields CIIR UMass

11/13 Michael Jordan Chinese restaurant process priors for graphical models UC-Berkeley

11/06 David Jensen Information Awareness: A Prospective Technical Assessment KDL UMass

10/23 Brendan Burns Opportunities for Machine Learning in Path Planning LPR UMass

10/16 Alvaro Bolivar Relevance Models: An application in the Real World CIIR UMass

10/16 Aron Culotta Relation extraction using tree kernels IESL UMass

10/16 Gary Huang Trend Detection and Entity Identification IESL UMass

10/09 Mohammad Ghavamzadeh Hierarchical Policy Gradient Algorithms ALL UMass

10/02 Amy McGovern Untangling Multiple-Instance Learning KDL UMass

09/25 Rob Platt Extending Fingertip Grasping to Whole Body Grasping LPR UMass

09/18 Balaraman Ravindran Hierarchical Reinforcement Learning ALL UMass

09/11 Rod Grupen A Developmental Organization for Robot Behavior LPR UMass

SUMMER 2003

Date Speaker Abstract Lab Institution

07/31 Daniel Bernstein Contract Algorithms and Robots on Rays: Unifying Two Scheduling Problems RBR UMass

07/24 R. Manmatha Automatic Image Annotation and Retrieval using Cross-Media Relevance Models CIIR UMass

07/03 Fuchun Peng Latent Maximum Entropy: A new approach to mixture model estimation CIIR UMass

06/12 Fernando Pereira Shallow Parsing with Conditional Random Fields plus an overview of recent work in Bioinformatics at UPenn UPenn

SPRING 2003

Date Speaker Abstract Lab Institution

05/08 Zhengzhu Feng Symbolic Generalization for On-line Planning RBR UMass

05/01 Dr. Leon Peshkin DYNAMIC BAYESIAN NETS FOR LANGUAGE MODELING Harvard

04/24 Ping Ji Modeling Frame-level Errors in GSM Wireless Channels CNRG UMass

04/17 Anita Raja Meta-Level Control in Bounded-Rational Agents MAS UMass

04/10 Victor Lavrenko Density Allocation for Modeling Discrete Data CIIR UMass

04/03 Michael T. Rosenstein SUPERVISED ACTOR-CRITIC REINFORCEMENT LEARNING ALL UMass

03/27 Jennifer Neville Learning Relational Probability Trees KDL UMass