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» Using model knowledge for learning inverse dynamics
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KDD
1997
ACM
109views Data Mining» more  KDD 1997»
15 years 7 months ago
Beyond Concise and Colorful: Learning Intelligible Rules
A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to understand data by discovering useful ...
Michael J. Pazzani, Subramani Mani, William Rodman...
143
Voted
ICML
2005
IEEE
16 years 4 months ago
Exploration and apprenticeship learning in reinforcement learning
We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
Pieter Abbeel, Andrew Y. Ng
183
Voted
PSIVT
2007
Springer
354views Multimedia» more  PSIVT 2007»
15 years 9 months ago
Real-Time Hand Gesture Detection and Recognition Using Boosted Classifiers and Active Learning
In this article a robust and real-time hand gesture detection and recognition system for dynamic environments is proposed. The system is based on the use of boosted classifiers for...
Hardy Francke, Javier Ruiz-del-Solar, Rodrigo Vers...
111
Voted
PARMA
2004
162views Database» more  PARMA 2004»
15 years 4 months ago
UML-based Conceptual Modeling of Pattern-Bases
The concept of pattern, meant as an interesting knowledge artifact extracted from data, is considered to be a an effective answer to the advanced analysis requirements emerging in ...
Stefano Rizzi
PAMI
2008
161views more  PAMI 2008»
15 years 3 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...