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ICML2009 Student Scholarship Recipients

We are delighted this year to be able to support an extensive student scholarship program. Each student received Registration and Travel support. This program has been made possible by the very generous support of the National Science Foundation (NSF), with additional support from our sponsors.

Abdeslma Boularias. Predictive Representations for Policy Gradient in POMDPs. [summary]

Ilya Sustskever. A simpler unified analysis of Budget Perceptrons. [summary]

Maksims Volkovs. BoltzRank: Learning to Maximize Expected Ranking Gain. [summary]

Gerhard Neumann. Learning Complex Motions by Sequencing Simpler Motion Templates. [summary]

Laurent Jacob. Group Lasso with Overlap and Graph Lasso. [summary]

Arpad Rimmel. Bandit-Based Optimization on Graphs with Application to Library Performance Tuning. [summary]

Stefanie Jegelka. Solution Stability in Linear Programming Relaxations: Graph Partitioning and Unsupervised Learning.. [summary]

Jonas Peters. Detecting the Direction of Causal Time Series. [summary]

Nino Shervashidze. The graphlet spectrum. [summary]

Weiwei Cheng. Decision tree and instance-based learning for label ranking. [No summary]

Jens Huhn. Decision tree and instance-based learning for label ranking. [summary]

Jason Pazis. Binary Action Search for Learning Continuous-Action Control Policies. [summary]

Marc Deisenroth. Analytic Moment-based Gaussian Process Filtering. [summary]

Eduardo Gomes. Dynamic Analysis of Multiagent Q-learning with e-greedy Exploration. [summary]

Vincent Nguyen. Information Theoretic Measures for Clusterings Comparison: Is a Correction for Chance Necessary?[summary]

Yanyan Lan. Generalization Analysis of Listwise Learning-to-Rank Algorithms. [summary]

Xiao Yuan. Robust Feature Extraction via Information Theoretic Learning. [summary]

Yu Li. Semi-Supervised Learning Using Label Mean. [summary]

De Zhan. Learning Instance Specific Distances Using Metric Propagation. [summary]

Rakesh Babu. More generality in efficient multiple kernel learning. [summary]

Zhuang Jinfeng. SimpleNPKL : Simple Non-Parametric Kernel Learning. [summary]

Duan Lixin. Domain Adaptation from Multiple Sources via Auxiliary Classifiers. [summary]

Jianhui Chen. A Convex Formulation for Learning Shared Structures from Multiple Tasks. [summary]

Shuiwang Ji. An Accelerated Gradient Method for Trace Norm Minimization. [summary]

Liang Sun. A Least Squares Formulation for a Class of Generalized Eigenvalue Problems in Machine Learning. [summary]

Amr Ahmed. MedLDA: Maximum Margin Sueprvised Topic Models for Regression and Classification. [summary]

Frederic de Mesmay. Bandit-Based Optimization on Graphs with Application to Library Performance Tuning. [summary]

Jonathan Huang. Probabilistic Reasoning with Permutations. [summary]

Tzu Huang. Learning Linear Dynamical Systems without Sequence Information. [summary]

Hetunandan Kamisetty. A Bayesian Approach to Protein Model Quality Assessment. [summary]

Andre Martins. Polyhedral Outer Approximations with Application to Natural Language Parsing . [summary]

Liu Yang. Online Learning by Ellipsoid Method. [summary]

Nikos Karampatziakis. Learning Prediction Suffix Trees with Winnow. [summary]

Yisong Yue. Interactively Optimizing Information Retrieval Systems as a Dueling Bandits Problem . [summary]

Wei Pan. Unsupervised Hierarchical Modeling of Locomotion Styles. [summary]

David Andrzejewski. Incorporating Domain Knowledge into Topic Modeling via Dirichlet Forest Priors. [summary]

Chih Cheng. Matrix Updates for Perceptron Training of Continuous Density Hidden Markov Models. [summary]

Youngmin Cho. Learning dictionaries of stable autoregressive models for audio scene analysis. [summary]

Brian McFee. Partial Order Embedding with Multiple Kernels. [summary]

Sushmita Roy. Learning Structurally Consistent Undirected Probabilistic Graphical Models. [summary]

Meghana Deodhar. A Scalable Framework for Discovering Coherent Co-clusters in Noisy Data. [summary]

Prateek Jain. Geometry-aware Metric Learning. [summary]

Christopher Painter-Wakefield. Linear Value Function Approximation and Linear Models. [summary]

George Kondaris. Skill Acquisition in Continuous Reinforcement Learning Domains. [summary]

Alicia Wolfe. Finding Equivalences Among Abstract Actions. [summary]

James MacGlashan. Hierarchical Skill Learning for High-Level Planning. [summary]

Todd Hester. An Empirical Comparison of Abstraction in Models of Markov Decision Processes. [summary]

Shivaram Kalyanakrishnan. Integrating Value Function-Based and Policy Search Methods for Sequential Decision Making. [summary]

Don Miner. Learning Non-Explicit Control Parameters of Swarm Systems. [summary]

Patricia Ordonez. Multivariate Time Series Analysis of Physiological and Clinical Data. [summary]

Marc Pickett. Autonomous Concept Formation from Undifferentiated Sensor Data. [summary]