ACML 2015

28 papers

A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections Ata Kaban

A Unified Framework for Jointly Learning Distributed Representations of Word and Attributes Liqiang Niu, Xin-Yu Dai, Shujian Huang, Jiajun Chen

Autoencoder Trees Ozan İrsoy, Ethem Alpaydin

Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias Yohei Kondo, Shin-ichi Maeda, Kohei Hayashi

Budgeted Bandit Problems with Continuous Random Costs Yingce Xia, Wenkui Ding, Xu-Dong Zhang, Nenghai Yu, Tao Qin

Class-Prior Estimation for Learning from Positive and Unlabeled Data Marthinus Christoffel, Gang Niu, Masashi Sugiyama

Consistency of Structured Output Learning with Missing Labels Kostiantyn Antoniuk, Vojtech Franc, Vaclav Hlavac

Continuous Target Shift Adaptation in Supervised Learning Tuan Duong Nguyen, Marthinus Christoffel, Masashi Sugiyama

Curriculum Learning of Bayesian Network Structures Yanpeng Zhao, Yetian Chen, Kewei Tu, Jin Tian

Data-Guided Approach for Learning and Improving User Experience in Computer Networks Yanan Bao, Xin Liu, Amit Pande

Detecting Accounting Frauds in Publicly Traded U.S. Firms: A Machine Learning Approach Bin Li, Julia Yu, Jie Zhang, Bin Ke

Expectation Propagation for Rectified Linear Poisson Regression Young-Jun Ko, Matthias W. Seeger

Geometry-Aware Principal Component Analysis for Symmetric Positive Definite Matrices Inbal Horev, Florian Yger, Masashi Sugiyama

Improving Sybil Detection via Graph Pruning and Regularization Techniques Huanhuan Zhang, Jie Zhang, Carol Fung, Chang Xu

Integration of Single-View Graphs with Diffusion of Tensor Product Graphs for Multi-View Spectral Clustering Le Shu, Longin Jan Latecki

Largest Source Subset Selection for Instance Transfer Shuang Zhou, Gijs Schoenmakers, Evgueni Smirnov, Ralf Peeters, Kurt Driessens, Siqi Chen

Maximum Margin Partial Label Learning Fei Yu, Min-Ling Zhang

Non-Asymptotic Analysis of Compressive Fisher Discriminants in Terms of the Effective Dimension Ata Kaban

One-Pass Multi-View Learning Yue Zhu, Wei Gao, Zhi-Hua Zhou

Preference Relation-Based Markov Random Fields for Recommender Systems Shaowu Liu, Gang Li, Truyen Tran, Yuan Jiang

Proximal Average Approximated Incremental Gradient Method for Composite Penalty Regularized Empirical Risk Minimization Yiu-ming Cheung, Jian Lou

Regularized Policy Gradients: Direct Variance Reduction in Policy Gradient Estimation Tingting Zhao, Gang Niu, Ning Xie, Jucheng Yang, Masashi Sugiyama

Robust Multivariate Regression with Grossly Corrupted Observations and Its Application to Personality Prediction Xiaowei Zhang, Li Cheng, Tingshao Zhu

Similarity-Based Contrastive Divergence Methods for Energy-Based Deep Learning Models Adepu Ravi Sankar, Vineeth N Balasubramanian

Statistical Unfolded Logic Learning Wang-Zhou Dai, Zhi-Hua Zhou

Streaming Variational Inference for Dirichlet Process Mixtures Viet Huynh, Dinh Phung, Svetha Venkatesh

Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities Hiroaki Sasaki, Voot Tangkaratt, Masashi Sugiyama

Surrogate Regret Bounds for Generalized Classification Performance Metrics Wojciech Kotlowski, Krzysztof Dembczyński