conftrace_

ACML 2011

23 papers

Mapping Kernels Defined Over Countably Infinite Mapping Systems and their Application

Kilho Shin

Summarization of Yes/No Questions Using a Feature Function Model

Jing He, Decheng Dai

Acceleration Technique for Boosting Classification and its Application to Face Detection

Masanori Kawakita, Ryota Izumi, Jun'ichi Takeuchi, Yi Hu, Tetsuya Takamori

Multi-label Active Learning with Auxiliary Learner

Chen-Wei Hung, Hsuan-tien Lin

Estimating Diffusion Probability Changes for AsIC-SIS Model from Information Diffusion Results

Akihiro Koide, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda

Multi-label Classification with Error-correcting Codes

Chung-Sung Ferng, Hsuan-tien Lin

Learning Attribute-weighted Voter Model over Social Networks

Yuki Yamagishi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda

Computationally Efficient Sufficient Dimension Reduction via Squared-Loss Mutual Information

Makoto Yamada, Gang Niu, Jun Takagi, Masashi Sugiyama

Robust Generation of Dynamical Patterns in Human Motion by a Deep Belief Nets

Sainbaya Sukhbaatar, Takaki Makino, Kazuyuki Aihara, Takashi Chikayama

Mixed-Variate Restricted Boltzmann Machines

Truyen Tran, Dinh Phung, Svetha Venkatesh

Learning Rules from Incomplete Examples via Implicit Mention Models

Janardhan Rao Doppa, Mohammad Shahed Sorower, Mohammad Nasresfahani, Jed Irvine, Walker Orr

Learning low-rank output kernels

Francesco Dinuzzo, Kenji Fukumizu

Approximate Model Selection for Large Scale LSSVM

Lizhong Ding, Shizhong Liao

Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization

Raphael Bailly

Unsupervised Multiple Kernel Learning

Jinfeng Zhuang, Jialei Wang, Steven C. H. Hoi, Xiangyang Lan

A General Linear Non-Gaussian State-Space Model: Identifiability, Identification, and Applications

Kun Zhang, Aapo Hyvärinen

Support Vector Machines Under Adversarial Label Noise

Battista Biggio, Blaine Nelson, Pavel Laskov

Bayesian Inference for Statistical Abduction Using Markov Chain Monte Carlo

Masakuzu Ishihata, Taisuke Sato

Microbagging Estimators: An Ensemble Approach to Distance-weighted Classifiers

Blaine Nelson, Battista Biggio, Pavel Laskov

Learning to Locate Relative Outliers

Shukai Li, Ivor W. Tsang

Nonlinear Online Classification Algorithm with Probability Margin

Mingmin Chi, Huijun He, Wenqiang Zhang

Continuous Rapid Action Value Estimates

Adrien Couëtoux, Mario Milone, Mátyás Brendel, Hassan Doghmen, Michele Sebag

Improving Policy Gradient Estimates with Influence Information

Jervis Pinto, Alan Fern, Tim Bauer, Martin Erwig