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ML
2007
ACM
131views Machine Learning» more  ML 2007»
15 years 5 months ago
A primal-dual perspective of online learning algorithms
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Shai Shalev-Shwartz, Yoram Singer
CVPR
2008
IEEE
16 years 8 months ago
Fast image search for learned metrics
We introduce a method that enables scalable image search for learned metrics. Given pairwise similarity and dissimilarity constraints between some images, we learn a Mahalanobis d...
Prateek Jain, Brian Kulis, Kristen Grauman
CGO
2009
IEEE
16 years 1 months ago
Automatic Feature Generation for Machine Learning Based Optimizing Compilation
Recent work has shown that machine learning can automate and in some cases outperform hand crafted compiler optimizations. Central to such an approach is that machine learning tec...
Hugh Leather, Edwin V. Bonilla, Michael O'Boyle
ITS
2010
Springer
178views Multimedia» more  ITS 2010»
15 years 11 months ago
Learning by Teaching SimStudent
The purpose of the current study was to test whether we could create a system where students can learn by teaching a live machine-learning agent. SimStudent is a computer agent tha...
Noboru Matsuda, Victoria Keiser, Rohan Raizada, Ga...
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 10 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone