Student Paper Awards
Every year, NIPS selects a small number of papers to receive the Best Student Paper Award. The goal of this award is to promote excellence in student research, and to acknowledge some of the most outstanding work published at NIPS.
For a paper to be eligible, at least fifty percent of the research reported in the paper must be performed by one or more student authors, and the student must agree to present the paper at the Conference. The awards are selected by a subcommittee of the program committee shortly before the Conference. The selection is based on the quality, originality, and clarity of the submission and its expected future impact. A list of winners in previous years follows:
NIPS 2009
Outstanding Student Paper Awards:
Menachem Fromer, Amir Globerson
An LP View of the M-Best MAP Problem
Nino Shervashidze, Karsten Borgwardt
Fast Subtree Kernels on Graphs
Honorable Mentions:
Jonathan Chang, Jordan Boyd-Graber, Sean Gerrish, Chong Wang, David Blei
Reading Tea Leaves: How Humans Interpret Topic Models
Daniel Hsu, Sham Kakade, John Langford, Tong Zhang
Multi-Label Prediction via Compressed Sensing
Bharath Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert Lanckriet, Bernhard Schoelkopf
Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions
NIPS 2008
Outstanding Student Paper Awards:
Markus Maier, Ulrike von Luxburg, Matthias Hein
Influence of Graph Construction on Graph-Based Clustering Measures
Srikanth Jagabathula, Devavrat Shah
Inferring Rankings under Constrained Sensing
Honorable Mentions:
Gediminas Luksys, Carmen Sandl,Wulfram Gerstner
Stress, Noradrenaline, and Realistic Prediction of Mouse Behaviour Using Reinforcement Learning
Lars Büsing, Benjamin Schrauwen, Robert Legenstein
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
NIPS 2007
Outstanding Student Paper Awards:
Adam Sanborn and Thomas Griffiths
Markov Chain Monte Carlo with People
David Sontag and Tommi Jaakkola
New Outer Bounds on the Marginal Polytope
Honorable Mentions 2007:
Misha Ahrens and Maneesh Sahani
Inferring Elaspsed Time from Stochastic Neural Processes
Jonathan Huang, Carlos Guestrin, and Leonidas Guibas
Efficient Inference for Distributions on Permutations
Pawan Mudigonda, Vladimir Kologorov, and Philip Torr
An Analysis of Convex Relaxations for MAP Estimation
NIPS 2006
Outstanding Student Paper Awards:
Ce Liu, William Freeman, and Edward Adelson
Analysis of Contour Motions
Fei Sha and Lawrence Saul
Large Margin Hidden Markov Models for Automatic Speech Recognition
Analysis of Empirical Bayesian Methods for Neuroelectromagnetic/
Source Localization
David Wipf, Rey Ramirez, Jason Palmer, Scott Mekeig, and Bhaskar Rao
Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization
Honorable Mentions 2006:
Charles Kemp, Patrick Shafto, Allison Berke, and Joshua Tenenbaum
Combining Causal and Similarity-Based Reasoning
Jeremy Lewi, Robert Butera, and Liam Paninski
Real-time Adaptive Information-Theoretic Optimization of
Neurobiological Experiments
Jennifer Listgarten, Radford Neal, Sam Roweis, Rachel Puckrin, and Sean Cutler
Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure
Michael Rabbat, Mario A.T. Figueiredo, and Robert Nowak
Inferring Network Structure from Co-Occurrences
NIPS 2005
Outstanding Student Paper Awards:
Keiji Miura, Masato Okada, and Shun-ichi Amari
Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing Environments
Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer
The Forgetron: A Kernel-Based Perceptron on a Fixed Budget
Patrick Flaherty, Michael Jordan, and Adam Arkin
Robust Design of Biological Experiments
Yael Niv, Nathaniel Daw, and Peter Dayan
How Fast to Work: Response Vigor, Motivation and Tonic Dopamine
NIPS 2004
Outstanding Student Papers:
Aaron C. Courville, Nathaniel D. Daw, and David Touretzky
Similarity and Discrimination in Classical Conditioning: A Latent Variable Account
Ulrike Von Luxburg,Olivier Bousquet, and Mikhail Belkin
Limits of Spectral Clustering
Amir Globerson, Gal Chechik, Fernando Pereira, and Naftali Tishby
Euclidean Embedding of Co-Occurence Data
Alexander T. Ihler, John W. Fisher, and Alan S. Willsky
Message Errors in Belief Propagation
NIPS 2003
Best Student Paper Awards:
Thomas Griffiths and Joshua Tenenbaum
From Algorithmic to Subjective Randomness
Liam Paninski, Jonathan Pillow, and Eero Simoncelli
Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model
David Blei, Thomas Griffifths, Michael Jordan and Joshua Tenenbaum
Hierarchical Topic Models and the Nested Chinese Restaurant Process
Carlos Guestrin, Ben Taskar and Daphne Koller
Max-Margin Markov Networks
NIPS 2002
Best Student Paper Award:
Ben Wegbreit, Brian Taba and Kwabena Boahen
Topographic Map Formation by Silicon Growth Cones
Honorable Mention:
Glenn M. Fung, Olvi L. Mangasarian, and Jude W. Shavlik
Knowledge-Based Support Vector Machine Classifier
Honorable Mention:
Anat Levin, Assaf Zomet and Yair Weiss
Learning to Perceive Transparency from the Statistics of Natural Scenes
Honorable Mention:
Neville E. Sanjana and Joshua B. Tenenbaum
Bayesian Models of Inductive Generalization
Special Award -- Most Original Submission:
Doudou LaLoudouana and Mambobo Bonouliqui
Tarare Data Set Selection
NIPS 2001
Best Student Paper Award:
Evan Greensmith, Peter L. Bartlett and Jonathan Baxter
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Honorable Mention:
Odelia Schwartz, E.J. Chichilnisky, and Eero P. Simoncelli
Characterizing Neural Gain Control Using Spike-triggered Covariance
Honorable Mention:
Martin Wainwright, T. Jaakkola, and A. Willsky
Tree-based Reparameterization for Approximate Estimation in Loopy Graphs
NIPS 2000
Athene Corporation Best Student Paper Award:
Lehel Csato and Manfred Opper
Sparse Representation for Gaussian Process Models
Honorable Mention:
Martijn A.R. Leisink and Hilbert J. Kappen
A Tighter Bound for Graphical Models
Honorable Mention:
Brian Sallans and Geoffrey E. Hinton
Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task