Zador's classic result for the asymptotic high-rate behavior of entropy-constrained vector quantization is recast in a Lagrangian form which better matches the Lloyd algorith...
Compressed Counting (CC) was recently proposed for approximating the th frequency moments of data streams, for 0 < 2. Under the relaxed strict-Turnstile model, CC dramaticall...
We present a learning framework for Markovian decision processes that is based on optimization in the policy space. Instead of using relatively slow gradient-based optimization al...
We propose a technique for measuring the structural similarity of semistructured documents based on entropy. After extracting the structural information from two documents we use ...
Maximum entropy models are a common modeling technique, but prone to overfitting. We show that using an exponential distribution as a prior leads to bounded absolute discounting b...