Sciweavers

NIPS
2007
14 years 1 months ago
Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion
We consider apprenticeship learning—learning from expert demonstrations—in the setting of large, complex domains. Past work in apprenticeship learning requires that the expert...
J. Zico Kolter, Pieter Abbeel, Andrew Y. Ng
NIPS
2007
14 years 1 months ago
Anytime Induction of Cost-sensitive Trees
Machine learning techniques are increasingly being used to produce a wide-range of classifiers for complex real-world applications that involve nonuniform testing costs and miscl...
Saher Esmeir, Shaul Markovitch
NIPS
2007
14 years 1 months ago
Privacy-Preserving Belief Propagation and Sampling
We provide provably privacy-preserving versions of belief propagation, Gibbs sampling, and other local algorithms — distributed multiparty protocols in which each party or verte...
Michael Kearns, Jinsong Tan, Jennifer Wortman
NIPS
2007
14 years 1 months ago
Semi-Supervised Multitask Learning
A semi-supervised multitask learning (MTL) framework is presented, in which M parameterized semi-supervised classifiers, each associated with one of M partially labeled data mani...
Qiuhua Liu, Xuejun Liao, Lawrence Carin
NIPS
2007
14 years 1 months ago
Boosting Algorithms for Maximizing the Soft Margin
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...
NIPS
2007
14 years 1 months ago
Parallelizing Support Vector Machines on Distributed Computers
Support Vector Machines (SVMs) suffer from a widely recognized scalability problem in both memory use and computational time. To improve scalability, we have developed a parallel ...
Edward Y. Chang, Kaihua Zhu, Hao Wang, Hongjie Bai...
NIPS
2007
14 years 1 months ago
Cooled and Relaxed Survey Propagation for MRFs
We describe a new algorithm, Relaxed Survey Propagation (RSP), for finding MAP configurations in Markov random fields. We compare its performance with state-of-the-art algorith...
Hai Leong Chieu, Wee Sun Lee, Yee Whye Teh
NIPS
2007
14 years 1 months ago
A general agnostic active learning algorithm
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...
Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni
NIPS
2007
14 years 1 months ago
Modeling Natural Sounds with Modulation Cascade Processes
Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences (∼1 s); phonemes (...
Richard Turner, Maneesh Sahani