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CVPR
2012
IEEE
13 years 7 months ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
ICML
2002
IEEE
16 years 5 months ago
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Carlos Guestrin, Relu Patrascu, Dale Schuurmans
281
Voted
KDD
2008
ACM
159views Data Mining» more  KDD 2008»
16 years 5 months ago
Semi-supervised learning with data calibration for long-term time series forecasting
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
Haibin Cheng, Pang-Ning Tan
HICSS
2003
IEEE
106views Biometrics» more  HICSS 2003»
15 years 10 months ago
Is web-based seminar an effective way of learning in adult education?
The Internet can be used to solve pedagogical problems. To give an example, seminars for crowded courses exceeding a hundred participants would not be possible without web-based a...
Pekka Makkonen
AROBOTS
2007
159views more  AROBOTS 2007»
15 years 4 months ago
Structure-based color learning on a mobile robot under changing illumination
— A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomo...
Mohan Sridharan, Peter Stone