ACML 2017

41 papers

NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks

Ermao Cai, Da-Cheng Juan, Dimitrios Stamoulis, Diana Marculescu

A Covariance Matrix Adaptation Evolution Strategy for Direct Policy Search in Reproducing Kernel Hilbert Space

Ngo Anh Vien, Viet-Hung Dang, TaeChoong Chung

Attentive Path Combination for Knowledge Graph Completion

Xiaotian Jiang, Quan Wang, Baoyuan Qi, Yongqin Qiu, Peng Li

Recovering Probability Distributions from Missing Data

Jin Tian

Radical-level Ideograph Encoder for RNN-based Sentiment Analysis of Chinese and Japanese

Yuanzhi Ke, Masafumi Hagiwara

On the Flatness of Loss Surface for Two-layered ReLU Networks

Jiezhang Cao, Qingyao Wu, Yuguang Yan, Li Wang, Mingkui Tan

Nested LSTMs

Joel Ruben Antony Moniz, David Krueger

Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms

Chao Ma, Janardhan Rao Doppa, Prasad Tadepalli, Hamed Shahbazi, Xiaoli Fern

Learning RBM with a DC programming Approach

Vidyadhar Upadhya, P. S. Sastry

Pyramid Person Matching Network for Person Re-identification

Chaojie Mao, Yingming Li, Zhongfei Zhang, Yaqing Zhang, Xi Li

Learning Deep Semantic Embeddings for Cross-Modal Retrieval

Cuicui Kang, Shengcai Liao, Zhen Li, Zigang Cao, Gang Xiong

A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings

Sami Remes, Markus Heinonen, Samuel Kaski

Accumulated Gradient Normalization

Joeri R. Hermans, Gerasimos Spanakis, Rico Möckel

A Word Embeddings Informed Focused Topic Model

He Zhao, Lan Du, Wray Buntine

Magnitude-Preserving Ranking for Structured Outputs

Céline Brouard, Eric Bach, Sebastian Böcker, Juho Rousu

Semi-supervised Convolutional Neural Networks for Identifying Wi-Fi Interference Sources

Krista Longi, Teemu Pulkkinen, Arto Klami

Whitening-Free Least-Squares Non-Gaussian Component Analysis

Hiroaki Shiino, Hiroaki Sasaki, Gang Niu, Masashi Sugiyama

Computer Assisted Composition with Recurrent Neural Networks

Christian Walder, Dongwoo Kim

One Class Splitting Criteria for Random Forests

Nicolas Goix, Nicolas Drougard, Romain Brault, Mael Chiapino

Recognizing Art Style Automatically in Painting with Deep Learning

Adrian Lecoutre, Benjamin Negrevergne, Florian Yger

Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications

Rongrong Zhang, Wei Deng, Michael Yu Zhu

Scale-Invariant Recognition by Weight-Shared CNNs in Parallel

Ryo Takahashi, Takashi Matsubara, Kuniaki Uehara

Regret for Expected Improvement over the Best-Observed Value and Stopping Condition

Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh

Deep Competitive Pathway Networks

Jia-Ren Chang, Yong-Sheng Chen

ST-GAN: Unsupervised Facial Image Semantic Transformation Using Generative Adversarial Networks

Jichao Zhang, Fan Zhong, Gongze Cao, Xueying Qin

Adaptive Sampling Scheme for Learning in Severely Imbalanced Large Scale Data

Wei Zhang, Said Kobeissi, Scott Tomko, Chris Challis

PHD: A Probabilistic Model of Hybrid Deep Collaborative Filtering for Recommender Systems

Jie Liu, Dong Wang, Yue Ding

Rate Optimal Estimation for High Dimensional Spatial Covariance Matrices

Yi Li, Aidong Adam Ding, Jennifer Dy

Data sparse nonparametric regression with $ε$-insensitive losses

Maxime Sangnier, Olivier Fercoq, Florence d’Alché-Buc

Locally Smoothed Neural Networks

Liang Pang, Yanyan Lan, Jun Xu, Jiafeng Guo, Xueqi Cheng

Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks

Magda Gregorová, Alexandros Kalousis, Stephane Marchand-Maillet

Probability Calibration Trees

Tim Leathart, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer

Select-and-Evaluate: A Learning Framework for Large-Scale Knowledge Graph Search

F A Rezaur Rahman Chowdhury, Chao Ma, Md Rakibul Islam, Mohammad Hossein Namaki, Mohammad Omar Faruk

Multi-view Clustering with Adaptively Learned Graph

Hong Tao, Chenping Hou, Jubo Zhu, Dongyun Yi

Distributionally Robust Groupwise Regularization Estimator

Jose Blanchet, Yang Kang

A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors

Zeke Xie, Issei Sato

Instance Specific Discriminative Modal Pursuit: A Serialized Approach

Yang Yang, De-Chuan Zhan, Ying Fan, Yuan Jiang

Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems

Vinod Kumar Chauhan, Kalpana Dahiya, Anuj Sharma

A Study on Trust Region Update Rules in Newton Methods for Large-scale Linear Classification

Chih-Yang Hsia, Ya Zhu, Chih-Jen Lin

Limits of End-to-End Learning

Tobias Glasmachers

Learning Convolutional Neural Networks using Hybrid Orthogonal Projection and Estimation

Hengyue Pan, Hui Jiang