Sciweavers

ICML
2010
IEEE
13 years 5 months ago
Forgetting Counts: Constant Memory Inference for a Dependent Hierarchical Pitman-Yor Process
We propose a novel dependent hierarchical Pitman-Yor process model for discrete data. An incremental Monte Carlo inference procedure for this model is developed. We show that infe...
Nicholas Bartlett, David Pfau, Frank Wood
ICML
2010
IEEE
13 years 5 months ago
Convergence of Least Squares Temporal Difference Methods Under General Conditions
We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...
Huizhen Yu
ICML
2010
IEEE
13 years 5 months ago
Budgeted Distribution Learning of Belief Net Parameters
Liuyang Li, Barnabás Póczos, Csaba S...
ICML
2010
IEEE
13 years 5 months ago
Submodular Dictionary Selection for Sparse Representation
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
Andreas Krause, Volkan Cevher
ICML
2010
IEEE
13 years 5 months ago
A Language-based Approach to Measuring Scholarly Impact
Identifying the most influential documents in a corpus is an important problem in many fields, from information science and historiography to text summarization and news aggregati...
Sean Gerrish, David M. Blei
ICML
2010
IEEE
13 years 5 months ago
Feature Selection as a One-Player Game
This paper formalizes Feature Selection as a Reinforcement Learning problem, leading to a provably optimal though intractable selection policy. As a second contribution, this pape...
Romaric Gaudel, Michèle Sebag
ICML
2010
IEEE
13 years 5 months ago
Robust Subspace Segmentation by Low-Rank Representation
We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank represe...
Guangcan Liu, Zhouchen Lin, Yong Yu
ICML
2010
IEEE
13 years 5 months ago
Gaussian Process Change Point Models
We combine Bayesian online change point detection with Gaussian processes to create a nonparametric time series model which can handle change points. The model can be used to loca...
Yunus Saatci, Ryan Turner, Carl Edward Rasmussen
ICML
2010
IEEE
13 years 5 months ago
On learning with kernels for unordered pairs
We propose and analyze two strategies to learn over unordered pairs with kernels, and provide a common theoretical framework to compare them. The strategies are related to methods...
Martial Hue, Jean-Philippe Vert
ICML
2010
IEEE
13 years 5 months ago
Distance dependent Chinese restaurant processes
We develop the distance dependent Chinese restaurant process (CRP), a flexible class of distributions over partitions that allows for nonexchangeability. This class can be used to...
David M. Blei, Peter Frazier