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ICML
1994
IEEE
15 years 10 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
145
Voted
KDD
2010
ACM
275views Data Mining» more  KDD 2010»
15 years 10 months ago
Combined regression and ranking
Many real-world data mining tasks require the achievement of two distinct goals when applied to unseen data: first, to induce an accurate preference ranking, and second to give g...
D. Sculley
181
Voted
CAV
2010
Springer
190views Hardware» more  CAV 2010»
15 years 10 months ago
Measuring and Synthesizing Systems in Probabilistic Environments
Often one has a preference order among the different systems that satisfy a given specification. Under a probabilistic assumption about the possible inputs, such a preference order...
Krishnendu Chatterjee, Thomas A. Henzinger, Barbar...
FAST
2010
15 years 9 months ago
A Clean-Slate Look at Disk Scrubbing
A number of techniques have been proposed to reduce the risk of data loss in hard-drives, from redundant disks (e.g., RAID systems) to error coding within individual drives. Disk ...
Alina Oprea, Ari Juels
FLAIRS
2010
15 years 9 months ago
Learning to Identify and Track Imaginary Objects Implied by Gestures
A vision-based machine learner is presented that learns characteristic hand and object movement patterns for using certain objects, and uses this information to recreate the "...
Andreya Piplica, Alexandra Olivier, Allison Petros...
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