Proceedings
All of the proceeding files(zip) are available here.
Contents
Preface | i |
Jorma Rissanen, Teemu Roos & Petri Myllymäki | ||
Entropy in Models for Estimation | 1 |
Teemu Roos | ||
Information capacity of full-body movements | 2 |
Joachim M. Buhmann | ||
What is the information content of an algorithm? | 3 |
Joe Suzuki | ||
The MDL principle for arbitrary data:either discrete or continuous or none of them | 4 |
Ionut Schiopu & Ioan Tăbuş | ||
Lossless contour compression using chain-code representations and context tree coding | 6 |
Ioan Tăbuş & Jorma Rissanen | ||
Time- and space-varying context tree models for image coding and analysis | 14 |
Nicolò Cesa-Bianchi | ||
Bandits without Regrets: The Power of Adaptive Adversaries | 15 |
Junya Honda | ||
Regret Analysis of a Bandit Problem for Normal Distributions with Unknown Means and Variances | 16 |
Taiji Suzuki | ||
Dual Averaging and Proximal Gradient Descent for Online Alternating Direction Multiplier Method | 17 |
Jesus Enrique Garcia & Verónica Andrea González-López | ||
Estimating the structure of interacting coordinates for a multivariate stochastic process | 18 |
Noboru Murata, Kensuke Koshijima & Hideitsu Hino | ||
Distance-based Change-Point Detection with Entropy Estimation | 22 |
Kenji Yamanishi & Hiroki Kanazawa | ||
Stochastic Complexity for Piecewise Stationary Memoryless Sources | 26 |
Jesus Enrique Garcia & Verónica Andrea González-López | ||
Detecting Regime Changes In Markov Models | 27 |
Narayana Prasad Santhanam | ||
Estimation in Markov processes | 31 |
Jun'ichi Takeuchi | ||
Asymptotically Minimax Prediction for Markov Sources | 32 |
Eiji Takimoto | ||
Combinatorial online prediction by continuous relaxation | 33 |
Toshiyuki Tanaka | ||
Compressed sensing and minimax denoising | 34 |
Sanghee Cho & Andrew Barron | ||
Approximate Iterative Bayes Optimal Estimates for High-Rate Sparse Superposition Codes | 35 |
Cynthia Rush & Andrew Barron | ||
Using the Method of Nearby Measures in Superposition Coding with a Bernoulli Dictionary | 43 |
Shiro Ikeda | ||
Optimization of probability measure and its applications in information theory | 49 |
Ryota Tomioka | ||
Convex Optimization for Tensor Decomposition | 50 |
Wray Buntine | ||
The flow of information in networks of probability vectors | 54 |
Shigeki Miyake & Hitoshi Asaeda | ||
Network Coding and Its Application to Content Centric Networking | 55 |
Fumiyasu Komaki | ||
Bayesian predictive densities when the distributions of data and target variables are different | 62 |
Kazuho Watanabe, Teemu Roos & Petri Myllymäki | ||
Achievability of Asymptotic Minimax Optimality in Online and Batch Coding | 63 |
Xiao Grace Yang & Andrew Barron | ||
Large Alphabet Coding And Prediction Through Poissonization And Titling | 68 |
Joseph A. O'Sullivan | ||
Information Bounds and Poisson Inference | 75 |
Michael U. Gutmann & Aapo Hyvärinen | ||
Estimation of unnormalized statistical models without numerical integration | 76 |
Ralf Eggeling, Teemu Roos, Petri Myllymäki & Ivo Grosse | ||
Model Selection In a Setting With Latent Variables | 84 |
Keisuke Yamazaki | ||
Distribution-Based Estimation of theLatent Variables and its Accuracy | 87 |
Sumio Watanabe | ||
WAIC and WBIC are Information Criteria for Singular Statistical Model Evaluation | 90 |