We address the problem of automatically learning object models for recognition and pose estimation. In contrast to the traditional approach, we formulate the recognition problem a...
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
In this paper, we describe a novel bidding strategy that autonomous trading agents can use to participate in Continuous Double Auctions (CDAs). Our strategy is based on both short...
Perukrishnen Vytelingum, Dave Cliff, Nicholas R. J...