ACML 2020

54 papers

Towards Understanding and Improving the Transferability of Adversarial Examples in Deep Neural Networks

Lei Wu, Zhanxing Zhu

Localizing and Amortizing: Efficient Inference for Gaussian Processes

Linfeng Liu, Liping Liu

A New Representation Learning Method for Individual Treatment Effect Estimation: Split Covariate Representation Network

Liu Qidong, Tian Feng, Ji Weihua, Zheng Qinghua

A foreground detection algorithm for Time-of-Flight cameras adapted dynamic integration time adjustment and multipath distortions

Detong Chen

Robust Deep Ordinal Regression under Label Noise

Bhanu Garg, Naresh Manwani

PSForest: Improving Deep Forest via Feature Pooling and Error Screening

Shiwen Ni, Hung-Yu Kao

Scalable Calibration of Affinity Matrices from Incomplete Observations

Wenye Li

Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis

Alexander Tornede, Marcel Wever, Stefan Werner, Felix Mohr, Eyke Hüllermeier

Robust Document Distance with Wasserstein-Fisher-Rao metric

Zihao Wang, Datong Zhou, Ming Yang, Yong Zhang, Chenglong Rao

Scaling up Simhash

Rameshwar Pratap, Anup Deshmukh, Pratheeksha Nair, Anirudh Ravi

Randomness Efficient Feature Hashing for Sparse Binary Data

Rameshwar Pratap, Karthik Revanuru, Anirudh Ravi, Raghav Kulkarni

Scalable Inference on the Soft Affiliation Graph Model for Overlapping Community Detection

Nishma Laitonjam, Weipeng Huang, Neil J. Hurley

Proxy Network for Few Shot Learning

Bin Xiao, Chien-Liang Liu, Wen-Hoar Hsaio

Partially Observable Markov Decision Process Modelling for Assessing Hierarchies

Weipeng Huang, Guangyuan Piao, Raul Moreno, Neil Hurley

Polytime Decomposition of Generalized Submodular Base Polytopes with Efficient Sampling

Aadirupa Saha

Network Representation Learning Algorithm Based on Neighborhood Influence Sequence

Meng Liu, Ziwei Quan, Yong Liu

NENN: Incorporate Node and Edge Features in Graph Neural Networks

Yulei Yang, Dongsheng Li

Monte-Carlo Graph Search: the Value of Merging Similar States

Edouard Leurent, Odalric-ambrym Maillard

MetAL: Active Semi-Supervised Learning on Graphs via Meta-Learning

Kaushalya Madhawa, Tsuyoshi Murata

Thompson Sampling for Unsupervised Sequential Selection

Arun Verma, Manjesh K Hanawal, Nandyala Hemachandra

Learning Interpretable Models using Soft Integrity Constraints

Khaled Belahcène, Nataliya Sokolovska, Yann Chevaleyre, Jean-Daniel Zucker

Learning from Label Proportions with Consistency Regularization

Kuen-Han Tsai, Hsuan-tien Lin

Learning Dynamic Context Graph Embedding

Chuanchang Chen, Yubo Tao, Hai Lin

Learning Code Changes by Exploiting Bidirectional Converting Deviation

Jia-Wei Mi, Shu-Ting Shi, Ming Li

Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning

Paulo R d O Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay

Inverse Visual Question Answering with Multi-Level Attentions

Yaser Alwattar, Yuhong Guo

Inferring Continuous Treatment Doses from Historical Data via Model-Based Entropy-Regularized Reinforcement Learning

Jianxun Wang, David Roberts, Andinet Enquobahrie

Geodesically-convex optimization for averaging partially observed covariance matrices

Florian Yger, Sylvain Chevallier, Quentin Barthélemy, Suvrit Sra

Foolproof Cooperative Learning

Alexis Jacq, Julien Pérolat, Matthieu Geist, Olivier Pietquin

FIREPruning: Learning-based Filter Pruning for Convolutional Neural Network Compression

Yuchu Fang, Wenzhong Li, Yao Zeng, Sanglu Lu

Exact Passive-Aggressive Algorithms for Multiclass Classification Using Bandit Feedbacks

Maanik Arora, Naresh Manwani

Enhancing Topic Models by Incorporating Explicit and Implicit External Knowledge

Yang Hong, Xinhuai Tang, Tiancheng Tang, Yunlong Hu, Jintai Tian

Efficient Attention Calibration Network for Real-Time Semantic Segmentation

Hengfeng Zha, Rui Liu, Dongsheng Zhou, Xin Yang, Qiang Zhang

Dual Learning: Theoretical Study and an Algorithmic Extension

Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-yan Liu

Disentangled Representations for Sequence Data using Information Bottleneck Principle

Masanori Yamada, Heecheol Kim, Kosuke Miyoshi, Tomoharu Iwata, Hiroshi Yamakawa

DFQF: Data Free Quantization-aware Fine-tuning

Bowen Li, Kai Huang, Siang Chen, Dongliang Xiong, Haitian Jiang

Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning

Sourya Dey, Saikrishna C. Kanala, Keith M. Chugg, Peter A. Beerel

Deep Dynamic Boosted Forest

Haixin Wang, Xingzhang Ren, Jinan Sun, Wei Ye, Long Chen

Data-Dependent Conversion to a Compact Integer-Weighted Representation of a Weighted Voting Classifier

Mitsuki Maekawa, Atsuyoshi Nakamura, Mineichi Kudo

Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization

Anas Barakat, Pascal Bianchi

Constrained Reinforcement Learning via Policy Splitting

Haoxian Chen, Henry Lam, Fengpei Li, Amirhossein Meisami

Collaborative Exploration in Stochastic Multi-Player Bandits

Hiba Dakdouk, Raphaël Féraud, Nadège Varsier, Patrick Maillé

CCA-Flow: Deep Multi-view Subspace Learning with Inverse Autoregressive Flow

Jia He, Feiyang Pan, Fuzhen Zhuang, Qing He

Bridging Ordinary-Label Learning and Complementary-Label Learning

Yasuhiro Katsura, Masato Uchida

Boosting-Based Reliable Model Reuse

Yao-Xiang Ding, Zhi-Hua Zhou

Bidirectional Dependency-Guided Attention for Relation Extraction

Xingchen Deng, Lei Zhang, Yixing Fan, Long Bai, Jiafeng Guo

Atlas-aware ConvNet for Accurate yet Robust Anatomical Segmentation

Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang

AARM: Action Attention Recalibration Module for Action Recognition

Li Zhonghong, Yi Yang, She Ying, Song Jialun, Wu Yukun

A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning

Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak

A One-step Approach to Covariate Shift Adaptation

Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama

A Novel Higher-order Weisfeiler-Lehman Graph Convolution

Clemens Damke, Vitalik Melnikov, Eyke Hüllermeier

Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning

Dung Nguyen, Svetha Venkatesh, Phuoc Nguyen, Truyen Tran

Semantic-Guided Shared Feature Alignment for Occluded Person Re-IDentification

Xuena Ren, Dongming Zhang, Xiuguo Bao

A Distance-Weighted Class-Homogeneous Neighbourhood Ratio for Algorithm Selection

Haofei Chen, Ya Liu, Japnit Kaur Ahuja, Daren Ler