NIPS
2001
13 years 11 months ago
2001
When a client interacts with an expert, e.g. a doctor, it falls upon the expert to ask questions that steer the process towards fulfilling the client's needs. This is most ef...
NIPS
2001
13 years 11 months ago
2001
The mystery of belief propagation (BP) decoder, especially of the turbo decoding, is studied from information geometrical viewpoint. The loopy belief network (BN) of turbo codes m...
NIPS
2001
13 years 11 months ago
2001
Mutual information is widely used, in a descriptive way, to measure the stochastic dependence of categorical random variables. In order to address questions such as the reliabilit...
NIPS
2001
13 years 11 months ago
2001
We propose a novel clustering method that is an extension of ideas inherent to scale-space clustering and support-vector clustering. Like the latter, it associates every data poin...
NIPS
2001
13 years 11 months ago
2001
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
NIPS
2001
13 years 11 months ago
2001
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
NIPS
2001
13 years 11 months ago
2001
Integration in the head-direction system is a computation by which horizontal angular head velocity signals from the vestibular nuclei are integrated to yield a neural representat...
NIPS
2001
13 years 11 months ago
2001
We present a principled and efficient planning algorithm for cooperative multiagent dynamic systems. A striking feature of our method is that the coordination and communication be...
NIPS
2001
13 years 11 months ago
2001
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
NIPS
2001
13 years 11 months ago
2001
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...