Proceedings
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 | |