COLT
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. The Gram matrix plays a central role in many kernel methods. Knowledge about the distribution of eigenvalues of the Gram matrix is useful for developing appropriate model...
COLT
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. We consider the problem of estimating an unknown probability distribution from samples using the principle of maximum entropy (maxent). To alleviate overfitting with a v...
COLT
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. We show several PAC-style concentration bounds for learning unigrams language model. One interesting quantity is the probability of all words appearing exactly k times in...
COLT
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. Probabilistic finite automata (PFA) model stochastic languages, i.e. probability distributions over strings. Inferring PFA from stochastic data is an open field of rese...
COLT
2004
Springer
13 years 10 months ago
2004
Springer
Abstract— We prove that given a nearly log-concave distribution, in any partition of the space to two well separated sets, the measure of the points that do not belong to these s...
COLT
2004
Springer
13 years 10 months ago
2004
Springer
We give the first polynomial time prediction strategy for any PAC-learnable class C that probabilistically predicts the target with mistake probability poly(log(t)) t = ˜O 1 t w...
COLT
2004
Springer
13 years 10 months ago
2004
Springer
COLT
2004
Springer
13 years 10 months ago
2004
Springer
We consider the problem of learning a general graph using edge-detecting queries. In this model, the learner may query whether a set of vertices induces an edge of the hidden grap...
COLT
2004
Springer
13 years 10 months ago
2004
Springer
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
COLT
2004
Springer
13 years 10 months ago
2004
Springer
We define the problem of inferring a “mixture of Markov chains” based on observing a stream of interleaved outputs from these chains. We show a sharp characterization of the i...