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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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142
Voted
ALT
1999
Springer
15 years 4 months ago
Extended Stochastic Complexity and Minimax Relative Loss Analysis
We are concerned with the problem of sequential prediction using a givenhypothesis class of continuously-manyprediction strategies. An e ectiveperformance measure is the minimax re...
Kenji Yamanishi
CIKM
2009
Springer
15 years 4 months ago
Classification-based resource selection
In some retrieval situations, a system must search across multiple collections. This task, referred to as federated search, occurs for example when searching a distributed index o...
Jaime Arguello, Jamie Callan, Fernando Diaz
117
Voted
ICML
2010
IEEE
15 years 1 months ago
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multiarmed bandit problem, where the payoff function is ...
Niranjan Srinivas, Andreas Krause, Sham Kakade, Ma...
ICML
2010
IEEE
15 years 1 months ago
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zi...
ICCV
2009
IEEE
16 years 5 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...