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» On Learning Limiting Programs
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AROBOTS
1999
104views more  AROBOTS 1999»
15 years 6 months ago
Reinforcement Learning Soccer Teams with Incomplete World Models
We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
Marco Wiering, Rafal Salustowicz, Jürgen Schm...
MT
2002
118views more  MT 2002»
15 years 6 months ago
MT for Minority Languages Using Elicitation-Based Learning of Syntactic Transfer Rules
The AVENUE project contains a run-time machine translation program that is surrounded by pre- and post-run-time modules. The post-run-time module selects among translation alternat...
Katharina Probst, Lori S. Levin, Erik Peterson, Al...
JMLR
2010
125views more  JMLR 2010»
15 years 1 months ago
Continuous Time Bayesian Network Reasoning and Learning Engine
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a co...
Christian R. Shelton, Yu Fan, William Lam, Joon Le...
ESOP
2009
Springer
16 years 1 months ago
Amortised Memory Analysis Using the Depth of Data Structures
Hofmann and Jost have presented a heap space analysis [1] that finds linear space bounds for many functional programs. It uses an amortised analysis: assigning hypothetical amount...
Brian Campbell
ICCV
2009
IEEE
16 years 12 months ago
Constrained Clustering by Spectral Kernel Learning
Clustering performance can often be greatly improved by leveraging side information. In this paper, we consider constrained clustering with pairwise constraints, which specify s...
Zhenguo Li, Jianzhuang Liu