2020 IJCAI 接受论文 list 分类排列(二)丶Java教程网-IT开发者们...

来自 : www.liangzl.com/get-article-de 发布时间：2021-03-24

A Bi-level Formulation for Label Noise Learning with Spectral Cluster Discovery
Yijing Luo, Bo Han, Chen Gong
A Dual Input-aware Factorization Machine for CTR Prediction
Wantong Lu, Yantao Yu, Yongzhe Chang, Zhen Wang, Chenhui Li, Bo Yuan
A Graphical and Attentional Framework for Dual-Target Cross-Domain Recommendation
Feng Zhu, Yan Wang, Chaochao Chen, Guanfeng Liu, Xiaolin Zheng
A new attention mechanism to classify multivariate time series
Yifan Hao, Huiping Cao
Accelerating Stratified Sampling SGD by Reconstructing Strata
Weijie Liu, Hui Qian, Chao Zhang, Zebang Shen, Jiahao Xie, Nenggan Zheng
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search
Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, Jingren Zhou
Adaptively Multi-Objective Adversarial Training for Dialogue Generation
Xuemiao Zhang, Zhouxing Tan, Xiaoning Zhang, Yang Cao, Rui Yan
An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles
Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent
Bowen Weng, Huaqing Xiong, Yingbin Liang, Wei Zhang
Arbitrary Talking Face Generation via Attentional Audio-Visual Coherence Learning
Hao Zhu, Huaibo Huang, Yi Li, Aihua Zheng, Ran He
Argot: Generating Adversarial Readable Chinese Texts
Zihan Zhang, Mingxuan Liu, Chao Zhang, Yiming Zhang, Zhou Li, Qi Li, Haixin Duan, Donghong Sun
Asymmetric Distribution Measure for Few-shot Learning
Wenbin Li, Lei Wang, Jing Huo, Yinghuan Shi, Yang Gao, Jiebo Luo
BaKer-Nets: Bayesian Random Kernel Mapping Networks
Hui Xue, Zheng-Fan Wu
Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning
Ishan Durugkar, Elad Liebman, Peter Stone
Batch Decorrelation for Active Metric Learning
Priyadarshini Kumari, Ritesh Goru, Siddhartha Chaudhuri, Subhasis Chaudhuri
Bayesian Decision Process for Budget-efficient Crowdsourced Clustering
Xiaozhou Wang, Xi Chen, Qihang Lin, Weidong Liu
Bayesian Optimization using Pseudo-Points
Chao Qian, Hang Xiong, Ke Xue
BERT-INT:A BERT-based Interaction Model For Knowledge Graph Alignment
Xiaobin Tang, Jing Zhang, Bo Chen, Yang Yang, Hong Chen, Cuiping Li
Best Arm Identification in Spectral Bandits
Tomáš Kocák, Aurélien Garivier
Beyond Network Pruning: a Joint Search-and-Training Approach
Xiaotong Lu, Han Huang, Weisheng Dong, Xin Li, Guangming Shi
BRPO: Batch Residual Policy Optimization
Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier
Can Cross Entropy Loss Be Robust to Label Noise?
Lei Feng, Senlin Shu, Zhuoyi Lin, Fengmao Lv, Li Li, Bo An
CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network
Jie Wen, Zheng Zhang, Yong Xu, Bob Zhang, Lunke Fei, Guo-Sen Xie
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation
Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu
Class Prior Estimation in Active Positive and Unlabeled Learning
Lorenzo Perini, Vincent Vercruyssen, Jesse Davis
Classification with Rejection: Scaling Generative Classifiers with Supervised Deep Infomax
Xin Wang, Siu Ming Yiu
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks
Jinghui Chen, Dongruo Zhou, Yiqi Tang, Ziyan Yang, Yuan Cao, Quanquan Gu
Collaboration Based Multi-Label Propagation for Fraud Detection
Haobo Wang, Zhao Li, Jiaming Huang, Pengrui Hui, Weiwei Liu, Tianlei Hu, Gang Chen
Collaborative Self-Attention Network for Session-based Recommendation
Anjing Luo, Pengpeng Zhao, Yanchi Liu, Fuzhen Zhuang, Deqing Wang, Jiajie Xu, Junhua Fang, Victor S. Sheng
Coloring Graph Neural Networks for Node Disambiguation
George Dasoulas, Ludovic Dos Santos, Kevin Scaman, Aladin Virmaux
Combinatorial Multi-Armed Bandits with Concave Rewards and Fairness Constraints
Huanle Xu, Yang Liu, Wing Cheong Lau, Rui Li
Communicative Representation Learning on Attributed Molecular Graphs
Ying Song, Shuangjia Zheng, Zhangming Niu, Zhang-hua Fu, Yutong Lu, Yuedong Yang
Complete Bottom-Up Predicate Invention in Meta-Interpretive Learning
Céline Hocquette, Stephen H. Muggleton
Compressed Self-Attention for Deep Metric Learning with Low-Rank Approximation
Ziye Chen, Mingming Gong, Lingjuan Ge, Bo Du
Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge
Pinzhuo Tian, Lei Qi, Shaokang Dong, Yinghuan Shi, Yang Gao
Constrained Policy Improvement for Efficient Reinforcement Learning
Elad Sarafian, Aviv Tamar, Sarit Kraus
Contextualized Point-of-Interest Recommendation
Peng Han, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li, Hao Wang, Shuo Shang
Convolutional Neural Networks with Compression Complexity Pooling for Out-of-Distribution Image Detection
Sehun Yu, Dongha Lee, Hwanjo Yu
Crowdsourcing with Multiple-Source Knowledge Transfer
Guangyang Han, Jinzheng Tu, Guoxian Yu, Jun Wang, Carlotta Domeniconi
DACE: Distribution-Aware Counterfactual Explanation by Mixed-Integer Linear Optimization
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Hiroki Arimura
Decorrelated Clustering with Data Selection Bias
Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang
Deep Feedback Network for Recommendation
Ruobing Xie, Cheng Ling, Yalong Wang, Rui Wang, Feng Xia, Leyu Lin
Deep Latent Low-Rank Fusion Network for Progressive Subspace Discovery
Zhao Zhang, Jiahuan Ren, Zheng Zhang, Guangcan Liu
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction
Alexander Schulz, Fabian Hinder, Barbara Hammer
Diffusion Variational Autoencoders
Luis A. Perez Rey, Vlado Menkovski, Jim Portegies
Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks
Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen, Ngai-Man Cheung
Discovering Latent Class Labels for Multi-Label Learning
Jun Huang, Linchuan Xu, Jing Wang, Lei Feng, Kenji Yamanishi
Discovering Subsequence Patterns for Next POI Recommendation
Kangzhi Zhao, Yong Zhang, Hongzhi Yin, Jin Wang, Kai Zheng, Xiaofang Zhou, Chunxiao Xing
Discriminative Feature Selection via A Structured Sparse Subspace Learning Module
Zheng Wang, Feiping Nie, Lai Tian, Rong Wang, Xuelong Li
Disentangling Direct and Indirect Interactions in Polytomous Item Response Theory Models
Frank Nussbaum, Joachim Giesen
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search
Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang, Zhenguo Li, Yong Yu
Dual Policy Distillation
Kwei-Herng Lai, Daochen Zha, Yuening Li, Xia Hu
Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering
Tao Shen, Xiubo Geng, Guodong Long, Jing Jiang, Chengqi Zhang, Daxin Jiang
Efficient Deep Reinforcement Learning via Adaptive Policy Transfer
Tianpei Yang, Jianye Hao, Zhaopeng Meng, Zongzhang Zhang, Yujing Hu, Yingfeng Chen, Changjie Fan, Weixun Wang, Wulong Liu, Zhaodong Wang, Jiajie Peng
Embodied Multimodal Multitask Learning
Devendra Singh Chaplot, Lisa Lee, Ruslan Salakhutdinov, Devi Parikh, Dhruv Batra
EndCold: An End-to-End Framework for Cold Question Routing in Community Question Answering Services
Jiankai Sun, Jie Zhao, Huan Sun, Srinivasan Parthasarathy
Evaluating and Aggregating Feature-based Model Explanations
Umang Bhatt, Adrian Weller, José M. F. Moura
Explainable Inference on Sequential Data via Memory-Tracking
Biagio La Rosa, Roberto Capobianco, Daniele Nardi
Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability
Deng Pan, Xiangrui Li, Xin Li, Dongxiao Zhu
Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network
Haowen Fang, Amar Shrestha, Ziyi Zhao, Qinru Qiu
Exploring Parameter Space with Structured Noise for Meta-Reinforcement Learning
Hui Xu, Chong Zhang, Jiaxing Wang, Deqiang Ouyang, Yu Zheng, Jie Shao
Fairness-Aware Neural Rényi Minimization for Continuous Features
Vincent Grari, Sylvain Lamprier, Marcin Detyniecki
Feature Statistics Guided Efficient Filter Pruning
Hang Li, Chen Ma, Wei Xu, Xue Liu
Flow-based Intrinsic Curiosity Module
Hsuan-Kung Yang, Po-Han Chiang, Min-Fong Hong, Chun-Yi Lee
FNNC: Achieving Fairness through Neural Networks
Manisha Padala, Sujit Gujar
Fully Nested Neural Network for Adaptive Compression and Quantization
Yufei Cui, Ziquan Liu, Wuguannan Yao, Qiao Li, Antoni B. Chan, Tei-wei Kuo, Chun Jason Xue
General Purpose MRF Learning with Neural Network Potentials
Hao Xiong, Nicholas Ruozzi
Generalized Mean Estimation in Monte-Carlo Tree Search
Tuan Dam, Pascal Klink, Carlo D\'Eramo, Jan Peters, Joni Pajarinen
Generating Robust Audio Adversarial Examples with Temporal Dependency
Hongting Zhang, Pan Zhou, Qiben Yan, Xiao-Yang Liu
Gradient Perturbation is Underrated for Differentially Private Convex Optimization
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
Greedy Convex Ensemble
Thanh Tan Nguyen, Nan Ye, Peter Bartlett
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks
Maxime Wabartha, Audrey Durand, Vincent François-Lavet, Joelle Pineau
Human-Driven FOL Explanations of Deep Learning
Gabriele Ciravegna, Francesco Giannini, Marco Gori, Marco Maggini, Stefano Melacci
Hybrid Learning for Multi-agent Cooperation with Sub-optimal Demonstrations
Peixi Peng, Junliang Xing, Lili Cao
Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space
Xiao Zhang, Shizhong Liao
I²HRL: Interactive Influence-based Hierarchical Reinforcement Learning
Rundong Wang, Runsheng Yu, Bo An, Zinovi Rabinovich
I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations
Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang
Independent Skill Transfer for Deep Reinforcement Learning
Qiangxing Tian, Guanchu Wang, Jinxin Liu, Donglin Wang, Yachen Kang
Inference-Masked Loss for Deep Structured Output Learning
Quan Guo, Hossein Rajaby Faghihi, Yue Zhang, Andrzej Uszok, Parisa Kordjamshidi
Intent Preference Decoupling for User Representation on Online Recommender System
Zhaoyang Liu, Haokun Chen, Fei Sun, Xu Xie, Jinyang Gao, Bolin Ding, Yanyan Shen
Intention2Basket: A Neural Intention-driven Approach for Dynamic Next-basket Planning
Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet Orgun, Longbing Cao
Internal and Contextual Attention Network for Cold-start Multi-channel Matching in Recommendation
Ruobing Xie, Zhijie Qiu, Jun Rao, Yi Liu, Bo Zhang, Leyu Lin
Interpretable Models for Understanding Immersive Simulations
Nicholas Hoernle, Kobi Gal, Barbara Grosz, Leilah Lyons, Ada Ren, Andee Rubin
IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL
Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam
Is the Skip Connection Provable to Reform the Neural Network Loss Landscape?
Lifu Wang, Bo Shen, Ning Zhao, Zhiyuan Zhang
Joint Multi-view 2D Convolutional Neural Networks for 3D Object Classification
Jinglin Xu, Xiangsen Zhang, Wenbin Li, Xinwang Liu, Junwei Han
Joint Partial Optimal Transport for Open Set Domain Adaptation
Renjun Xu, Pelen Liu, Yin Zhang, Fang Cai, Jindong Wang, Shuoying Liang, Heting Ying, Jianwei Yin
KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction
Xuan Lin, Zhe Quan, Zhi-Jie Wang, Tengfei Ma, Xiangxiang Zeng
Knowledge Hypergraphs: Prediction Beyond Binary Relations
Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole
Knowledge-Based Regularization in Generative Modeling
Naoya Takeishi, Yoshinobu Kawahara
KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge
Peng Zhang, Jianye Hao, Weixun Wang, Hongyao Tang, Yi Ma, Yihai Duan, Yan Zheng
Label Distribution for Learning with Noisy Labels
Yun-Peng Liu, Ning Xu, Yu Zhang, Xin Geng
Label Enhancement for Label Distribution Learning via Prior Knowledge
Yongbiao Gao, Yu Zhang, Xin Geng
Learning and Solving Regular Decision Processes
Eden Abadi, Ronen I. Brafman
Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data
Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Marc Sebban
Learning From Multi-Dimensional Partial Labels
Haobo Wang, Weiwei Liu, Yang Zhao, Tianlei Hu, Ke Chen, Gang Chen
Learning in the Wild with Incremental Skeptical Gaussian Processes
Andrea Bontempelli, Stefano Teso, Fausto Giunchiglia, Andrea Passerini
Learning Interpretable Models in the Property Specification Language
Rajarshi Roy, Dana Fisman, Daniel Neider
Learning Interpretable Representations with Informative Entanglements
Ege Beyazıt, Doruk Tuncel, Xu Yuan, Nian-Feng Tzeng, Xindong Wu
Learning Large Logic Programs By Going Beyond Entailment
Andrew Cropper, Sebastijan Dumančic
Learning Neural-Symbolic Descriptive Planning Models via Cube-Space Priors: The Voyage Home (to STRIPS)
Masataro Asai, Christian Muise
Learning Personalized Itemset Mapping for Cross-Domain Recommendation
Yinan Zhang, Yong Liu, Peng Han, Chunyan Miao, Lizhen Cui, Baoli Li, Haihong Tang
Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data
Masahiro Kohjima, Takeshi Kurashima, Hiroyuki Toda
Learning With Subquadratic Regularization : A Primal-Dual Approach
Raman Sankaran, Francis Bach, Chiranjib Bhattacharyya
Location Prediction over Sparse User Mobility Traces Using RNNs: Flashback in Hidden States!
Dingqi Yang, Benjamin Fankhauser, Paolo Rosso, Philippe Cudre-Mauroux
Logic Constrained Pointer Networks for Interpretable Textual Similarity
Subhadeep Maji, Rohan Kumar, Manish Bansal, Kalyani Roy, Pawan Goyal
LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks
Rongzhou Huang, Chuyin Huang, Yubao Liu, Genan Dai, Weiyang Kong
MaCAR: Urban Traffic Light Control via Active Multi-agent Communication and Action Rectification
Zhengxu Yu, Shuxian Liang, Long Wei, Zhongming Jin, Jianqiang Huang, Deng Cai, Xiaofei He, Xian-Sheng Hua
Marthe: Scheduling the Learning Rate Via Online Hypergradients
Michele Donini, Luca Franceschi, Orchid Majumder, Massimiliano Pontil, Paolo Frasconi
Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications
Shujian Yu, Ammar Shaker, Francesco Alesiani, Jose Principe
Memory Augmented Neural Model for Incremental Session-based Recommendation
Fei Mi, Boi Faltings
MergeNAS: Merge Operations into One for Differentiable Architecture Search
Xiaoxing Wang, Chao Xue, Junchi Yan, Xiaokang Yang, Yonggang Hu, Kewei Sun
Metric Learning in Optimal Transport for Domain Adaptation
Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban
Mixed-Variable Bayesian Optimization
Erik Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause
Multi-Class Imbalanced Graph Convolutional Network Learning
Min Shi, Yufei Tang, Xingquan Zhu, David Wilson, Jianxun Liu
Multi-Feedback Bandit Learning with Probabilistic Contexts
Luting Yang, Jianyi Yang, Shaolei Ren
Multi-label Feature Selection via Global Relevance and Redundancy Optimization
Jia Zhang, Yidong Lin, Min Jiang, Shaozi Li, Yong Tang, Kay Chen Tan
Multi-Scale Group Transformer for Long Sequence Modeling in Speech Separation
Yucheng Zhao, Chong Luo, Zheng-Jun Zha, Wenjun Zeng
Multi-View Attribute Graph Convolution Networks for Clustering
Jiafeng Cheng, Qianqian Wang, Zhiqiang Tao, Deyan Xie, Quanxue Gao
MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse Environmental Dynamics
Mohammadamin Barekatain, Ryo Yonetani, Masashi Hamaya
Multivariate Probability Calibration with Isotonic Bernstein Polynomials
Yongqiao Wang, Xudong Liu
Mutual Information Estimation using LSH Sampling
Ryan Spring, Anshumali Shrivastava
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs
Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang
Neighbor Combinatorial Attention for Critical Structure Mining
Tanli Zuo, Yukun Qiu, Wei-Shi Zheng
Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals
Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag
Neural Tensor Model for Learning Multi-Aspect Factors in Recommender Systems
Huiyuan Chen, Jing Li
Non-monotone DR-submodular Maximization over General Convex Sets
Christoph Dürr, Nguyen Kim Thang, Abhinav Srivastav, Léo Tible
On Deep Unsupervised Active Learning
Changsheng Li, Handong Ma, Zhao Kang, Ye Yuan, Xiao-Yu Zhang, Guoren Wang
On Metric DBSCAN with Low Doubling Dimension
Hu Ding, Fan Yang, Mingyue Wang
One-Shot Neural Architecture Search via Novelty Driven Sampling
Miao Zhang, Huiqi Li, Shirui Pan, Taoping Liu, Steven Su
Online Positive and Unlabeled Learning
Chuang Zhang, Chen Gong, Tengfei Liu, Xun Lu, Weiqiang Wang, Jian Yang
Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL
Yannis Flet-Berliac, Philippe Preux
Optimal Margin Distribution Machine for Multi-Instance Learning
Teng Zhang, Hai Jin
Optimality, Accuracy, and Efficiency of an Exact Functional Test
Hien H. Nguyen, Hua Zhong, Mingzhou Song
Order-Dependent Event Models for Agent Interactions
Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian
P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection
Zhiwei Zhang, Shifeng Chen, Lei Sun
Partial Multi-Label Learning via Multi-Subspace Representation
Ziwei Li, Gengyu Lyu, Songhe Feng
pbSGD: Powered Stochastic Gradient Descent Methods for Accelerated Non-Convex Optimization
Beitong Zhou, Jun Liu, Weigao Sun, Ruijuan Chen, Claire Tomlin, Ye Yuan
Positive Unlabeled Learning with Class-prior Approximation
Shizhen Chang, Bo Du, Liangpei Zhang
Potential Driven Reinforcement Learning for Hard Exploration Tasks
Enmin Zhao, Shihong Deng, Yifan Zang, Yongxin Kang, Kai Li, Junliang Xing
Privileged label enhancement with multi-label learning
Wenfang Zhu, Xiuyi Jia, Weiwei Li
Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables
Jiaqi Zhang, Meng Wang, Qinchi Li, Sen Wang, Xiaojun Chang, Beilun Wang
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation
Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh
RDF-to-Text Generation with Graph-augmented Structural Neural Encoders
Hanning Gao, Lingfei Wu, Po Hu, Fangli Xu
Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling
Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Zheng Yu, Scott A. Sisson
Reducing Underflow in Mixed Precision Training by Gradient Scaling
Ruizhe Zhao, Brian Vogel, Tanvir Ahmed, Wayne Luk
Reinforcement Learning Framework for Deep Brain Stimulation Study
Dmitrii Krylov, Remi Tachet des Combes, Romain Laroche, Michael Rosenblum, Dmitry V. Dylov
Reinforcement Learning with Dynamic Boltzmann Softmax Updates
Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang
Reward Prediction Error as an Exploration Objective in Deep RL
Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, Sebastian Seung, Daniel Lee
Scalable Gaussian Process Regression Networks
Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe
Self-adaptive Re-weighted Adversarial Domain Adaptation
Shanshan Wang, Lei Zhang
Self-Attentional Credit Assignment for Transfer in Reinforcement Learning
Johan Ferret, Raphael Marinier, Matthieu Geist, Olivier Pietquin
Self-paced Consensus Clustering with Bipartite Graph
Peng Zhou, Liang Du, Xuejun Li
Semi-supervised Clustering via Pairwise Constrained Optimal Graph
Feiping Nie, Han Zhang, Rong Wang, Xuelong Li
Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling
Daniel Stoller, Mi Tian, Sebastian Ewert, Simon Dixon
SI-VDNAS: Semi-Implicit Variational Dropout for Hierarchical One-shot Neural Architecture Search
Yaoming Wang, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong
Sinkhorn Regression
Lei Luo, Jian Pei, Heng Huang
Smart Contract Vulnerability Detection using Graph Neural Network
Yuan Zhuang, Zhenguang Liu, Peng Qian, Qi Liu, Xiang Wang, Qinming He
Soft Threshold Ternary Networks
Weixiang Xu, Xiangyu He, Tianli Zhao, Qinghao Hu, Peisong Wang, Jian Cheng
Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning
Dieqiao Feng, Carla Gomes, Bart Selman
Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error
Taiji Suzuki, Hiroshi Abe, Tomoya Murata, Shingo Horiuchi, Kotaro Ito, Tokuma Wachi, So Hirai, Masatoshi Yukishima, Tomoaki Nishimura
Split to Be Slim: An Overlooked Redundancy in Vanilla Convolution
Qiulin Zhang, Zhuqing Jiang, Qishuo Lu, Jia\'nan Han, Zhengxin Zeng, Shanghua Gao, Aidong Men
Stabilizing Adversarial Invariance Induction from Divergence Minimization Perspective
Yusuke Iwasawa, Kei Akuzawa, Yutaka Matsuo
Stochastic Batch Augmentation with An Effective Distilled Dynamic Soft Label Regularizer
Qian Li, Qingyuan Hu, Yong Qi, Saiyu Qi, Jie Ma, Jian Zhang
SVRG for Policy Evaluation with Fewer Gradient Evaluations
Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup
Switching Poisson Gamma Dynamical Systems
Wenchao Chen, Bo Chen, Yicheng Liu, Qianru Zhao, Mingyuan Zhou
Synthesizing Aspect-Driven Recommendation Explanations from Reviews
Trung-Hoang Le, Hady W. Lauw
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution
Sankalp Garg, Navodita Sharma, Woojeong Jin, Xiang Ren
Tensor-based multi-view label enhancement for multi-label learning
Fangwen Zhang, Xiuyi Jia, Weiwei Li
Textual Membership Queries
Jonathan Zarecki, Shaul Markovitch
The Importance of the Test Set Size in Quantification Assessment
André Maletzke, Waqar Hassan, Denis dos Reis, Gustavo Batista
The Sparse MinMax k-Means Algorithm for High-Dimensional Clustering
Sayak Dey, Swagatam Das, Rammohan Mallipeddi
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation
Qinghua Ding, Kaiwen Zhou, James Cheng
Toward a neuro-inspired creative decoder
Payel Das, Brian Quanz, Pin-Yu Chen, Jae-wook Ahn, Dhruv Shah
Towards a Hierarchical Bayesian Model of Multi-View Anomaly Detection
Zhen Wang, Chao Lan
Towards Accurate and Robust Domain Adaptation under Noisy Environments
Zhongyi Han, Xian-Jin Gui, Chaoran Cui, Yilong Yin
Towards Explainable Conversational Recommendation
Zhongxia Chen, Xiting Wang, Xing Xie, Mehul Parsana, Akshay Soni, Xiang Ao, Enhong Chen
Trajectory Similarity Learning with Auxiliary Supervision and Optimal Matching
Hanyuan Zhang, Xinyu Zhang, Qize Jiang, Baihua Zheng, Zhenbang Sun, Weiwei Sun, Changhu Wang
TransRHS: A Representation Learning Method for Knowledge Graphs with Relation Hierarchical Structure
Fuxiang Zhang, Xin Wang, Zhao Li, Jianxin Li
Triple-GAIL: A Multi-Modal Imitation Learning Framework with Generative Adversarial Nets
Cong Fei, Bin Wang, Yuzheng Zhuang, Zongzhang Zhang, Jianye Hao, Hongbo Zhang, Xuewu Ji, Wulong Liu
Understanding the Power and Limitations of Teaching with Imperfect Knowledge
Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla
Unsupervised Domain Adaptation with Dual-Scheme Fusion Network for Medical Image Segmentation
Danbing Zou, Qikui Zhu, Pingkun Yan
Unsupervised Monocular Visual-inertial Odometry Network
Peng Wei, Guoliang Hua, Weibo Huang, Fanyang Meng, Hong Liu
Unsupervised Representation Learning by Predicting Random Distances
Hu Wang, Guansong Pang, Chunhua Shen, Congbo Ma
User Modeling with Click Preference and Reading Satisfaction for News Recommendation
Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang
Variational Learning of Bayesian Neural Networks via Bayesian Dark Knowledge
Gehui Shen, Xi Chen, Zhihong Deng
Weakly-Supervised Multi-view Multi-instance Multi-label Learning
Yuying Xing, Guoxian Yu, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang