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ML
2002
ACM
154views Machine Learning» more  ML 2002»
13 years 7 months ago
Technical Update: Least-Squares Temporal Difference Learning
TD() is a popular family of algorithms for approximate policy evaluation in large MDPs. TD() works by incrementally updating the value function after each observed transition. It h...
Justin A. Boyan
JUCS
2008
104views more  JUCS 2008»
13 years 7 months ago
Optimal Transit Price Negotiation: The Distributed Learning Perspective
: We present a distributed learning algorithm for optimizing transit prices in the inter-domain routing framework. We present a combined game theoretical and distributed algorithmi...
Dominique Barth, Loubna Echabbi, Chahinez Hamlaoui
AAAI
2006
13 years 9 months ago
Reasoning about Partially Observed Actions
Partially observed actions are observations of action executions in which we are uncertain about the identity of objects, agents, or locations involved in the actions (e.g., we kn...
Megan Nance, Adam Vogel, Eyal Amir
ICASSP
2009
IEEE
14 years 2 months ago
A mixed time-scale algorithm for distributed parameter estimation : Nonlinear observation models and imperfect communication
Abstract— The paper considers the algorithm NLU for distributed (vector) parameter estimation in sensor networks, where, the local observation models are nonlinear, and inter-sen...
Soummya Kar, José M. F. Moura
NIPS
2008
13 years 9 months ago
An Homotopy Algorithm for the Lasso with Online Observations
It has been shown that the problem of 1-penalized least-square regression commonly referred to as the Lasso or Basis Pursuit DeNoising leads to solutions that are sparse and there...
Pierre Garrigues, Laurent El Ghaoui