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141
Voted
ICML
2010
IEEE
15 years 4 months ago
Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
Philip M. Long, Rocco A. Servedio
131
Voted
ICIP
2006
IEEE
16 years 5 months ago
Support Vector Machines for Camera Calibration Problem
This paper presents a statistical learning-based solution to the camera calibration problem in which the Support Vector Machines (SVM) are used for the estimation of the projectio...
Refaat M. Mohamed, Abdelrehim H. Ahmed, Ahmed Eid,...
142
Voted
IDA
2005
Springer
15 years 9 months ago
Learning from Ambiguously Labeled Examples
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Eyke Hüllermeier, Jürgen Beringer
139
Voted
ICML
2004
IEEE
16 years 4 months ago
Apprenticeship learning via inverse reinforcement learning
We consider learning in a Markov decision process where we are not explicitly given a reward function, but where instead we can observe an expert demonstrating the task that we wa...
Pieter Abbeel, Andrew Y. Ng
94
Voted
EMNLP
2008
15 years 5 months ago
Part-of-Speech Tagging for English-Spanish Code-Switched Text
Code-switching is an interesting linguistic phenomenon commonly observed in highly bilingual communities. It consists of mixing languages in the same conversational event. This pa...
Thamar Solorio, Yang Liu