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» Algorithms for induced biclique optimization problems
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KDD
2010
ACM
287views Data Mining» more  KDD 2010»
15 years 1 months ago
Designing efficient cascaded classifiers: tradeoff between accuracy and cost
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...
Vikas C. Raykar, Balaji Krishnapuram, Shipeng Yu
CVPR
2011
IEEE
14 years 9 months ago
Dynamic Batch Mode Active Learning
Active learning techniques have gained popularity in reducing human effort to annotate data instances for inducing a classifier. When faced with large quantities of unlabeled dat...
Shayok Chakraborty, Vineeth Balasubramanian, Sethu...
ACL
2006
15 years 1 months ago
Semantic Taxonomy Induction from Heterogenous Evidence
We propose a novel algorithm for inducing semantic taxonomies. Previous algorithms for taxonomy induction have typically focused on independent classifiers for discovering new sin...
Rion Snow, Daniel Jurafsky, Andrew Y. Ng
ECML
2006
Springer
15 years 3 months ago
Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
Sébastien Jodogne, Justus H. Piater
AINA
2006
IEEE
15 years 1 months ago
Distributed Tuning Attempt Probability for Data Gathering in Random Access Wireless Sensor Networks
In this paper, we study the problem of data gathering in multi-hop wireless sensor networks. To tackle the high degree of channel contention and high probability of packet collisi...
Haibo Zhang, Hong Shen