IJCAI 2019

964 papers

Not All FPRASs are Equal: Demystifying FPRASs for DNF-Counting (Extended Abstract)

Kuldeep S. Meel, Aditya A. Shrotri, Moshe Y. Vardi

Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms

Panagiotis Mandros, Mario Boley, Jilles Vreeken

Impact of Consuming Suggested Items on the Assessment of Recommendations in User Studies on Recommender Systems

Benedikt Loepp, Tim Donkers, Timm Kleemann, Jürgen Ziegler

Delayed Impact of Fair Machine Learning

Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt

A Walkthrough for the Principle of Logit Separation

Gil Keren, Sivan Sabato, Björn Schuller

Meta-Interpretive Learning Using HEX-Programs

Tobias Kaminski, Thomas Eiter, Katsumi Inoue

On Causal Identification under Markov Equivalence

Amin Jaber, Jiji Zhang, Elias Bareinboim

The Power of Context in Networks: Ideal Point Models with Social Interactions

Mohammad T. Irfan, Tucker Gordon

On Guiding Search in HTN Planning with Classical Planning Heuristics

Daniel Höller, Pascal Bercher, Gregor Behnke, Susanne Biundo

Clause Learning and New Bounds for Graph Coloring

Emmanuel Hebrard, George Katsirelos

The Provable Virtue of Laziness in Motion Planning

Nika Haghtalab, Simon Mackenzie, Ariel D. Procaccia, Oren Salzman, Siddhartha Srinivasa

A Dual Approach to Verify and Train Deep Networks

Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Timothy Mann, Pushmeet Kohli

Sharpness of the Satisfiability Threshold for Non-Uniform Random k-SAT

Tobias Friedrich, Ralf Rothenberger

Addressing Age-Related Bias in Sentiment Analysis

Mark Díaz, Isaac Johnson, Amanda Lazar, Anne Marie Piper, Darren Gergle

Do We Need Many-valued Logics for Incomplete Information?

Marco Console, Paolo Guagliardo, Leonid Libkin

Quality Control Attack Schemes in Crowdsourcing

Alessandro Checco, Jo Bates, Gianluca Demartini

Closed-World Semantics for Conjunctive Queries with Negation over ELH-bottom Ontologies

Stefan Borgwardt, Walter Forkel

A Refined Understanding of Cost-optimal Planning with Polytree Causal Graphs

Christer Bäckström, Peter Jonsson, Sebastian Ordyniak

Synthesizing Datalog Programs using Numerical Relaxation

Xujie Si, Mukund Raghothaman, Kihong Heo, Mayur Naik

How Well Do Machines Perform on IQ tests: a Comparison Study on a Large-Scale Dataset

Yusen Liu, Fangyuan He, Haodi Zhang, Guozheng Rao, Zhiyong Feng

EL Embeddings: Geometric Construction of Models for the Description Logic EL++

Maxat Kulmanov, Wang Liu-Wei, Yuan Yan, Robert Hoehndorf

Learning Hierarchical Symbolic Representations to Support Interactive Task Learning and Knowledge Transfer

James R. Kirk, John E. Laird

A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning

Sebastijan Dumancic, Alberto Garcia-Duran, Mathias Niepert

Learning Relational Representations with Auto-encoding Logic Programs

Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel

Playgol: Learning Programs Through Play

Andrew Cropper

LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning

Alberto Camacho, Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano, Sheila A. McIlraith

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection

Yuxi Zhou, Shenda Hong, Junyuan Shang, Meng Wu, Qingyun Wang

Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields

Yue Zhang, Arti Ramesh

A Decomposition Approach for Urban Anomaly Detection Across Spatiotemporal Data

Mingyang Zhang, Tong Li, Hongzhi Shi, Yong Li, Pan Hui

Balanced Ranking with Diversity Constraints

Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich

Automatic Grassland Degradation Estimation Using Deep Learning

Xiyu Yan, Yong Jiang, Shuai Chen, Zihao He, Chunmei Li

Who Should Pay the Cost: A Game-theoretic Model for Government Subsidized Investments to Improve National Cybersecurity

Xinrun Wang, Bo An, Hau Chan

Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses

Xiao Wang, Siyue Wang, Pin-Yu Chen, Yanzhi Wang, Brian Kulis

Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving

Akifumi Wachi

Group-Fairness in Influence Maximization

Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, Yair Zick

Bidirectional Active Learning with Gold-Instance-Based Human Training

Feilong Tang

Controllable Neural Story Plot Generation via Reward Shaping

Pradyumna Tambwekar, Murtaza Dhuliawala, Lara J. Martin, Animesh Mehta, Brent Harrison

Simultaneous Prediction Intervals for Patient-Specific Survival Curves

Samuel Sokota, Ryan D'Orazio, Khurram Javed, Humza Haider, Russell Greiner

Daytime Sleepiness Level Prediction Using Respiratory Information

Kazuhiko Shinoda, Masahiko Yoshii, Hayato Yamaguchi, Hirotaka Kaji

Three-quarter Sibling Regression for Denoising Observational Data

Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich

Pre-training of Graph Augmented Transformers for Medication Recommendation

Junyuan Shang, Tengfei Ma, Cao Xiao, Jimeng Sun

Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance

Wenjie Ruan, Min Wu, Youcheng Sun, Xiaowei Huang, Daniel Kroening

MNN: Multimodal Attentional Neural Networks for Diagnosis Prediction

Zhi Qiao, Xian Wu, Shen Ge, Wei Fan

KitcheNette: Predicting and Ranking Food Ingredient Pairings using Siamese Neural Network

Donghyeon Park, Keonwoo Kim, Yonggyu Park, Jungwoon Shin, Jaewoo Kang

Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies

Muhammad Masood, Finale Doshi-velez

Scribble-to-Painting Transformation with Multi-Task Generative Adversarial Networks

Jinning Li, Yexiang Xue

Truly Batch Apprenticeship Learning with Deep Successor Features

Donghun Lee, Srivatsan Srinivasan, Finale Doshi-velez

Systematic Conservation Planning for Sustainable Land-use Policies: A Constrained Partitioning Approach to Reserve Selection and Design.

Dimitri Justeau-Allaire, Philippe Vismara, Philippe Birnbaum, Xavier Lorca

RDPD: Rich Data Helps Poor Data via Imitation

Shenda Hong, Cao Xiao, Trong Nghia Hoang, Tengfei Ma, Hongyan Li

MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals

Shenda Hong, Cao Xiao, Tengfei Ma, Hongyan Li, Jimeng Sun

CounterFactual Regression with Importance Sampling Weights

Negar Hassanpour, Russell Greiner

mdfa: Multi-Differential Fairness Auditor for Black Box Classifiers

Xavier Gitiaux, Huzefa Rangwala

Improving Customer Satisfaction in Bike Sharing Systems through Dynamic Repositioning

Supriyo Ghosh, Jing Yu Koh, Patrick Jaillet

DDL: Deep Dictionary Learning for Predictive Phenotyping

Tianfan Fu, Trong Nghia Hoang, Cao Xiao, Jimeng Sun

Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning

Marcello Fiducioso, Sebastian Curi, Benedikt Schumacher, Markus Gwerder, Andreas Krause

Enhancing Stock Movement Prediction with Adversarial Training

Fuli Feng, Huimin Chen, Xiangnan He, Ji Ding, Maosong Sun

The Price of Local Fairness in Multistage Selection

Vitalii Emelianov, George Arvanitakis, Nicolas Gast, Krishna Gummadi, Patrick Loiseau

PI-Bully: Personalized Cyberbullying Detection with Peer Influence

Lu Cheng, Jundong Li, Yasin Silva, Deborah Hall, Huan Liu

Risk Assessment for Networked-guarantee Loans Using High-order Graph Attention Representation

Dawei Cheng, Yi Tu, Zhenwei Ma, Zhibin Niu, Liqing Zhang

Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization under Uncertainty

Jonathan Chase, Duc Thien Nguyen, Haiyang Sun, Hoong Chuin Lau

AI-powered Posture Training: Application of Machine Learning in Sitting Posture Recognition Using the LifeChair Smart Cushion

Katia Bourahmoune, Toshiyuki Amagasa

Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively

Serena Booth, Christian Muise, Julie Shah

Decision Making for Improving Maritime Traffic Safety Using Constraint Programming

Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau

Governance by Glass-Box: Implementing Transparent Moral Bounds for AI Behaviour

Andrea Aler Tubella, Andreas Theodorou, Frank Dignum, Virginia Dignum

SparseSense: Human Activity Recognition from Highly Sparse Sensor Data-streams Using Set-based Neural Networks

Alireza Abedin, S. Hamid Rezatofighi, Qinfeng Shi, Damith C. Ranasinghe

DiffChaser: Detecting Disagreements for Deep Neural Networks

Xiaofei Xie, Lei Ma, Haijun Wang, Yuekang Li, Yang Liu

ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation

Jing Song, Hong Shen, Zijing Ou, Junyi Zhang, Teng Xiao

Ranked Programming

Tjitze Rienstra

Cutset Bayesian Networks: A New Representation for Learning Rao-Blackwellised Graphical Models

Tahrima Rahman, Shasha Jin, Vibhav Gogate

Hyper-parameter Tuning under a Budget Constraint

Zhiyun Lu, Liyu Chen, Chao-Kai Chiang, Fei Sha

Exact Bernoulli Scan Statistics using Binary Decision Diagrams

Masakazu Ishihata, Takanori Maehara

An End-to-End Community Detection Model: Integrating LDA into Markov Random Field via Factor Graph

Dongxiao He, Wenze Song, Di Jin, Zhiyong Feng, Yuxiao Huang

On Constrained Open-World Probabilistic Databases

Tal Friedman, Guy Van den Broeck

Thompson Sampling on Symmetric Alpha-Stable Bandits

Abhimanyu Dubey, Alex `Sandy' Pentland

Bayesian Parameter Estimation for Nonlinear Dynamics Using Sensitivity Analysis

Yi Chou, Sriram Sankaranarayanan

Lifted Message Passing for Hybrid Probabilistic Inference

Yuqiao Chen, Nicholas Ruozzi, Sriraam Natarajan

Statistical Guarantees for the Robustness of Bayesian Neural Networks

Luca Cardelli, Marta Kwiatkowska, Luca Laurenti, Nicola Paoletti, Andrea Patane

Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos

Haofei Xu, Jianmin Zheng, Jianfei Cai, Juyong Zhang

Unsupervised Learning of Monocular Depth and Ego-Motion using Conditional PatchGANs

Madhu Vankadari, Swagat Kumar, Anima Majumder, Kaushik Das

The Parameterized Complexity of Motion Planning for Snake-Like Robots

Siddharth Gupta, Guy Sa'ar, Meirav Zehavi

Energy-Efficient Slithering Gait Exploration for a Snake-Like Robot Based on Reinforcement Learning

Zhenshan Bing, Christian Lemke, Zhuangyi Jiang, Kai Huang, Alois Knoll

Steady-State Policy Synthesis for Verifiable Control

Alvaro Velasquez

Merge-and-Shrink Task Reformulation for Classical Planning

Álvaro Torralba, Silvan Sievers

On Computational Complexity of Pickup-and-Delivery Problems with Precedence Constraints or Time Windows

Xing Tan, Jimmy Xiangji Huang

Scheduling Jobs with Stochastic Processing Time on Parallel Identical Machines

Richard Stec, Antonin Novak, Premysl Sucha, Zdenek Hanzalek

Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning

Jendrik Seipp

A Novel Distribution-Embedded Neural Network for Sensor-Based Activity Recognition

Hangwei Qian, Sinno Jialin Pan, Bingshui Da, Chunyan Miao

Adaptive Thompson Sampling Stacks for Memory Bounded Open-Loop Planning

Thomy Phan, Thomas Gabor, Robert Müller, Christoph Roch, Claudia Linnhoff-Popien

Partitioning Techniques in LTLf Synthesis

Lucas Martinelli Tabajara, Moshe Y. Vardi

Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations

Joseph Kim, Christian Muise, Ankit Shah, Shubham Agarwal, Julie Shah

Approximability of Constant-horizon Constrained POMDP

Majid Khonji, Ashkan Jasour, Brian Williams

Dynamic logic of parallel propositional assignments and its applications to planning

Andreas Herzig, Frédéric Maris, Julien Vianey

Fair Online Allocation of Perishable Goods and its Application to Electric Vehicle Charging

Enrico H. Gerding, Alvaro Perez-Diaz, Haris Aziz, Serge Gaspers, Antonia Marcu

Subgoal-Based Temporal Abstraction in Monte-Carlo Tree Search

Thomas Gabor, Jan Peter, Thomy Phan, Christian Meyer, Claudia Linnhoff-Popien

Generalized Potential Heuristics for Classical Planning

Guillem Francès, Augusto B. Corrêa, Cedric Geissmann, Florian Pommerening

Online Probabilistic Goal Recognition over Nominal Models

Ramon Fraga Pereira, Mor Vered, Felipe Meneguzzi, Miquel Ramirez

Influence of State-Variable Constraints on Partially Observable Monte Carlo Planning

Alberto Castellini, Georgios Chalkiadakis, Alessandro Farinelli

Counterexample-Guided Strategy Improvement for POMDPs Using Recurrent Neural Networks

Steven Carr, Nils Jansen, Ralf Wimmer, Alexandru Serban, Bernd Becker

Strong Fully Observable Non-Deterministic Planning with LTL and LTLf Goals

Alberto Camacho, Sheila A. McIlraith

Regular Decision Processes: A Model for Non-Markovian Domains

Ronen I. Brafman, Giuseppe De Giacomo