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9th ACML 2017: Seoul, Korea
- Min-Ling Zhang, Yung-Kyun Noh:
Proceedings of The 9th Asian Conference on Machine Learning, ACML 2017, Seoul, Korea, November 15-17, 2017. Proceedings of Machine Learning Research 77, PMLR 2017
Preface
- Preface. i-xv
Accepted Papers
- Hengyue Pan, Hui Jiang:
Learning Convolutional Neural Networks using Hybrid Orthogonal Projection and Estimation. 1-16 - Tobias Glasmachers:
Limits of End-to-End Learning. 17-32 - Chih-Yang Hsia, Ya Zhu, Chih-Jen Lin:
A Study on Trust Region Update Rules in Newton Methods for Large-scale Linear Classification. 33-48 - Vinod Kumar Chauhan, Kalpana Dahiya, Anuj Sharma:
Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems. 49-64 - Yang Yang, De-Chuan Zhan, Ying Fan, Yuan Jiang:
Instance Specific Discriminative Modal Pursuit: A Serialized Approach. 65-80 - Zeke Xie, Issei Sato:
A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors. 81-96 - Jose H. Blanchet, Yang Kang:
Distributionally Robust Groupwise Regularization Estimator. 97-112 - Hong Tao, Chenping Hou, Jubo Zhu, Dongyun Yi:
Multi-view Clustering with Adaptively Learned Graph. 113-128 - F. A. Rezaur Rahman Chowdhury, Chao Ma, Md. Rakibul Islam, Mohammad Hossein Namaki, Mohammad Omar Faruk, Janardhan Rao Doppa:
Select-and-Evaluate: A Learning Framework for Large-Scale Knowledge Graph Search. 129-144 - Tim Leathart, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer:
Probability Calibration Trees. 145-160 - Magda Gregorová
, Alexandros Kalousis, Stéphane Marchand-Maillet:
Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks. 161-176 - Liang Pang, Yanyan Lan, Jun Xu, Jiafeng Guo, Xueqi Cheng:
Locally Smoothed Neural Networks. 177-191 - Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc:
Data sparse nonparametric regression with ε-insensitive losses. 192-207 - Yi Li, Aidong Adam Ding, Jennifer G. Dy:
Rate Optimal Estimation for High Dimensional Spatial Covariance Matrices. 208-223 - Jie Liu, Dong Wang, Yue Ding:
PHD: A Probabilistic Model of Hybrid Deep Collaborative Filtering for Recommender Systems. 224-239 - Wei Zhang, Said Kobeissi, Scott Tomko, Chris Challis:
Adaptive Sampling Scheme for Learning in Severely Imbalanced Large Scale Data. 240-247 - Jichao Zhang, Fan Zhong, Gongze Cao, Xueying Qin:
ST-GAN: Unsupervised Facial Image Semantic Transformation Using Generative Adversarial Networks. 248-263 - Jia-Ren Chang, Yong-Sheng Chen:
Deep Competitive Pathway Networks. 264-278 - Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh
Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. 279-294 - Ryo Takahashi, Takashi Matsubara, Kuniaki Uehara:
Scale-Invariant Recognition by Weight-Shared CNNs in Parallel. 295-310 - Rongrong Zhang, Wei Deng, Yu Michael Zhu:
Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications. 311-326 - Adrian Lecoutre, Benjamin Négrevergne, Florian Yger:
Recognizing Art Style Automatically in Painting with Deep Learning. 327-342 - Nicolas Goix, Nicolas Drougard, Romain Brault, Maël Chiapino:
One Class Splitting Criteria for Random Forests. 343-358 - Christian J. Walder, Dongwoo Kim:
Computer Assisted Composition with Recurrent Neural Networks. 359-374 - Hiroaki Shiino, Hiroaki Sasaki, Gang Niu, Masashi Sugiyama:
Whitening-Free Least-Squares Non-Gaussian Component Analysis. 375-390 - Krista Longi, Teemu Pulkkinen, Arto Klami:
Semi-supervised Convolutional Neural Networks for Identifying Wi-Fi Interference Sources. 391-406 - Céline Brouard, Eric Bach, Sebastian Böcker
Magnitude-Preserving Ranking for Structured Outputs. 407-422 - He Zhao, Lan Du, Wray L. Buntine:
A Word Embeddings Informed Focused Topic Model. 423-438 - Joeri R. Hermans, Gerasimos Spanakis, Rico Möckel:
Accumulated Gradient Normalization. 439-454 - Sami Remes, Markus Heinonen, Samuel Kaski:
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings. 455-470 - Cuicui Kang, Shengcai Liao, Zhen Li, Zigang Cao, Gang Xiong:
Learning Deep Semantic Embeddings for Cross-Modal Retrieval. 471-486 - Chaojie Mao, Yingming Li, Zhongfei Zhang, Yaqing Zhang, Xi Li:
Pyramid Person Matching Network for Person Re-identification. 487-497 - Vidyadhar Upadhya, P. S. Sastry:
Learning RBM with a DC programming Approach. 498-513 - Chao Ma, Janardhan Rao Doppa, Prasad Tadepalli
Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms. 514-529 - Joel Ruben Antony Moniz, David Krueger:
Nested LSTMs. 530-544 - Jiezhang Cao, Qingyao Wu, Yuguang Yan, Li Wang, Mingkui Tan:
On the Flatness of Loss Surface for Two-layered ReLU Networks. 545-560 - Yuanzhi Ke, Masafumi Hagiwara:
Radical-level Ideograph Encoder for RNN-based Sentiment Analysis of Chinese and Japanese. 561-573 - Jin Tian:
Recovering Probability Distributions from Missing Data. 574-589 - Xiaotian Jiang, Quan Wang, Baoyuan Qi, Yongqin Qiu, Peng Li, Bin Wang:
Attentive Path Combination for Knowledge Graph Completion. 590-605 - Ngo Anh Vien, Viet-Hung Dang, TaeChoong Chung:
A Covariance Matrix Adaptation Evolution Strategy for Direct Policy Search in Reproducing Kernel Hilbert Space. 606-621 - Ermao Cai, Da-Cheng Juan, Dimitrios Stamoulis, Diana Marculescu:
\emphNeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks. 622-637
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