AAAI 2022

1,624 papers

Learning Logic Programs Though Divide, Constrain, and Conquer

Andrew Cropper

Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks

Francesco Croce, Maksym Andriushchenko, Naman D. Singh, Nicolas Flammarion, Matthias Hein

Reinforcement Learning with Stochastic Reward Machines

Jan Corazza, Ivan Gavran, Daniel Neider

Graph-Wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning

Thilini Cooray, Ngai-Man Cheung

Learning Influence Adoption in Heterogeneous Networks

Vincent Conitzer, Debmalya Panigrahi, Hanrui Zhang

Cody Coleman, Edward Chou, Julian Katz-Samuels, Sean Culatana, Peter Bailis

How to Distribute Data across Tasks for Meta-Learning?

Alexandru Cioba, Michael Bromberg, Qian Wang, Ritwik Niyogi, Georgios Batzolis

Learning by Competition of Self-Interested Reinforcement Learning Agents

Stephen Chung

Differentially Private Regret Minimization in Episodic Markov Decision Processes

Sayak Ray Chowdhury, Xingyu Zhou

Graph Neural Controlled Differential Equations for Traffic Forecasting

Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, Noseong Park

DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy

Anda Cheng, Jiaxing Wang, Xi Sheryl Zhang, Qiang Chen, Peisong Wang

Identification of Linear Latent Variable Model with Arbitrary Distribution

Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Kun Zhang

ASM2TV: An Adaptive Semi-supervised Multi-Task Multi-View Learning Framework for Human Activity Recognition

Zekai Chen, Xiao Zhang, Xiuzhen Cheng

BScNets: Block Simplicial Complex Neural Networks

Yuzhou Chen, Yulia R. Gel, H. Vincent Poor

KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-zero Training Loss

Yuhan Chen, Takashi Matsubara, Takaharu Yaguchi

Imbalance-Aware Uplift Modeling for Observational Data

Xuanying Chen, Zhining Liu, Li Yu, Liuyi Yao, Wenpeng Zhang

Multimodal Adversarially Learned Inference with Factorized Discriminators

Wenxue Chen, Jianke Zhu

Input-Specific Robustness Certification for Randomized Smoothing

Ruoxin Chen, Jie Li, Junchi Yan, Ping Li, Bin Sheng

Instance Selection: A Bayesian Decision Theory Perspective

Qingqiang Chen, Fuyuan Cao, Ying Xing, Jiye Liang

Semi-supervised Learning with Multi-Head Co-Training

Mingcai Chen, Yuntao Du, Yi Zhang, Shuwei Qian, Chongjun Wang

Zero Stability Well Predicts Performance of Convolutional Neural Networks

Liangming Chen, Long Jin, Mingsheng Shang

Evidential Neighborhood Contrastive Learning for Universal Domain Adaptation

Liang Chen, Yihang Lou, Jianzhong He, Tao Bai, Minghua Deng

Mutual Nearest Neighbor Contrast and Hybrid Prototype Self-Training for Universal Domain Adaptation

Liang Chen, Qianjin Du, Yihang Lou, Jianzhong He, Tao Bai

Better Parameter-Free Stochastic Optimization with ODE Updates for Coin-Betting

Keyi Chen, John Langford, Francesco Orabona

An Online Learning Approach to Sequential User-Centric Selection Problems

Junpu Chen, Hong Xie

Efficient Robust Training via Backward Smoothing

Jinghui Chen, Yu Cheng, Zhe Gan, Quanquan Gu, Jingjing Liu

Clustering Interval-Censored Time-Series for Disease Phenotyping

Irene Y. Chen, Rahul G. Krishnan, David Sontag

Simultaneously Learning Stochastic and Adversarial Bandits under the Position-Based Model

Cheng Chen, Canzhe Zhao, Shuai Li

Multiscale Generative Models: Improving Performance of a Generative Model Using Feedback from Other Dependent Generative Models

Changyu CHEN, Avinandan Bose, Shih-Fen Cheng, Arunesh Sinha

Deconvolutional Density Network: Modeling Free-Form Conditional Distributions

Bing Chen, Mazharul Islam, Jisuo Gao, Lin Wang

Safe Online Convex Optimization with Unknown Linear Safety Constraints

Sapana Chaudhary, Dileep Kalathil

Locally Private k-Means Clustering with Constant Multiplicative Approximation and Near-Optimal Additive Error

Anamay Chaturvedi, Matthew Jones, Huy Lê Nguyễn

A Unifying Theory of Thompson Sampling for Continuous Risk-Averse Bandits

Joel Q. L. Chang, Vincent Y. F. Tan

Active Sampling for Text Classification with Subinstance Level Queries

Shayok Chakraborty, Ankita Singh

Leaping through Time with Gradient-Based Adaptation for Recommendation

Nuttapong Chairatanakul, Hoang NT, Xin Liu, Tsuyoshi Murata

NoiseGrad — Enhancing Explanations by Introducing Stochasticity to Model Weights

Kirill Bykov, Anna Hedström, Shinichi Nakajima, Marina M.-C. Höhne

Shrub Ensembles for Online Classification

Sebastian Buschjäger, Sibylle Hess, Katharina J. Morik

Breaking the Convergence Barrier: Optimization via Fixed-Time Convergent Flows

Param Budhraja, Mayank Baranwal, Kunal Garg, Ashish Hota

Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs

Fanchen Bu, Dong Eui Chang

ErfAct and Pserf: Non-monotonic Smooth Trainable Activation Functions

Koushik Biswas, Sandeep Kumar, Shilpak Banerjee, Ashish Kumar Pandey

Robust and Resource-Efficient Data-Free Knowledge Distillation by Generative Pseudo Replay

Kuluhan Binici, Shivam Aggarwal, Nam Trung Pham, Karianto Leman, Tulika Mitra

Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better

Sameer Bibikar, Haris Vikalo, Zhangyang Wang, Xiaohan Chen

Modeling Attrition in Recommender Systems with Departing Bandits

Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary C. Lipton, Yishay Mansour

A Fast Algorithm for PAC Combinatorial Pure Exploration

Noa Ben-David, Sivan Sabato

Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis

Taha Belkhouja, Yan Yan, Janardhan Rao Doppa

Entropy-Based Logic Explanations of Neural Networks

Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori

Admissible Policy Teaching through Reward Design

Kiarash Banihashem, Adish Singla, Jiarui Gan, Goran Radanovic

Programmatic Modeling and Generation of Real-Time Strategic Soccer Environments for Reinforcement Learning

Abdus Salam Azad, Edward Kim, Qiancheng Wu, Kimin Lee, Ion Stoica

Beyond GNNs: An Efficient Architecture for Graph Problems

Pranjal Awasthi, Abhimanyu Das, Sreenivas Gollapudi

Latent Time Neural Ordinary Differential Equations

Srinivas Anumasa, P. K. Srijith

DeformRS: Certifying Input Deformations with Randomized Smoothing

Motasem Alfarra, Adel Bibi, Naeemullah Khan, Philip H.S. Torr, Bernard Ghanem

Combating Adversaries with Anti-adversaries

Motasem Alfarra, Juan C. Perez, Ali Thabet, Adel Bibi, Philip H.S. Torr

Private Rank Aggregation in Central and Local Models

Daniel Alabi, Badih Ghazi, Ravi Kumar, Pasin Manurangsi

Distributed Learning with Strategic Users: A Repeated Game Approach

Abdullah B Akbay, Junshan Zhang

FisheyeHDK: Hyperbolic Deformable Kernel Learning for Ultra-Wide Field-of-View Image Recognition

Ola Ahmad, Freddy Lecue

Context-Specific Representation Abstraction for Deep Option Learning

Marwa Abdulhai, Dong-Ki Kim, Matthew Riemer, Miao Liu, Gerald Tesauro

Characterizing the Program Expressive Power of Existential Rule Languages

Heng Zhang, Guifei Jiang

Hao Zhang, Shuigeng Zhou, Kun Zhang, Jihong Guan

Learning to Walk with Dual Agents for Knowledge Graph Reasoning

Denghui Zhang, Zixuan Yuan, Hao Liu, Xiaodong Lin, Hui Xiong

Inductive Relation Prediction by BERT

Hanwen Zha, Zhiyu Chen, Xifeng Yan

SGEITL: Scene Graph Enhanced Image-Text Learning for Visual Commonsense Reasoning

Zhecan Wang, Haoxuan You, Liunian Harold Li, Alireza Zareian, Suji Park

MeTeoR: Practical Reasoning in Datalog with Metric Temporal Operators

Dingmin Wang, Pan Hu, Przemysław Andrzej Wałęga, Bernardo Cuenca Grau

First Order Rewritability in Ontology-Mediated Querying in Horn Description Logics

David Toman, Grant Weddell

Weakly Supervised Neural Symbolic Learning for Cognitive Tasks

Jidong Tian, Yitian Li, Wenqing Chen, Liqiang Xiao, Hao He

On Paraconsistent Belief Revision in LP

Nicolas Schwind, Sébastien Konieczny, Ramón Pino Pérez

Random vs. Best-First: Impact of Sampling Strategies on Decision Making in Model-Based Diagnosis

Patrick Rodler

Propositional Encodings of Acyclicity and Reachability by Using Vertex Elimination

Masood Feyzbakhsh Rankooh, Jussi Rintanen

Knowledge Compilation Meets Logical Separability

Junming Qiu, Wenqing Li, Zhanhao Xiao, Quanlong Guan, Liangda Fang

Prevailing in the Dark: Information Walls in Strategic Games

Pavel Naumov, Wenxuan Zhang

Compilation of Aggregates in ASP Systems

Giuseppe Mazzotta, Francesco Ricca, Carmine Dodaro

TempoQR: Temporal Question Reasoning over Knowledge Graphs

Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Adesoji Adeshina, Phillip R Howard

Weighted Model Counting in FO2 with Cardinality Constraints and Counting Quantifiers: A Closed Form Formula

Sagar Malhotra, Luciano Serafini

Using Conditional Independence for Belief Revision

Matthew James Lynn, James P. Delgrande, Pavlos Peppas

Automated Synthesis of Generalized Invariant Strategies via Counterexample-Guided Strategy Refinement

Kailun Luo, Yongmei Liu

Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection

Ting Long, Yutong Xie, Xianyu Chen, Weinan Zhang, Qinxiang Cao

How Does Knowledge Graph Embedding Extrapolate to Unseen Data: A Semantic Evidence View

Ren Li, Yanan Cao, Qiannan Zhu, Guanqun Bi, Fang Fang

Bounds on Causal Effects and Application to High Dimensional Data

Ang Li, Judea Pearl

Unit Selection with Causal Diagram

Ang Li, Judea Pearl

ApproxASP – a Scalable Approximate Answer Set Counter

Mohimenul Kabir, Flavio O Everardo, Ankit K Shukla, Markus Hecher, Johannes Klaus Fichte

Towards Fine-Grained Reasoning for Fake News Detection

Yiqiao Jin, Xiting Wang, Ruichao Yang, Yizhou Sun, Wei Wang

Inferring Lexicographically-Ordered Rewards from Preferences

Alihan Hüyük, William R. Zame, Mihaela van der Schaar

Understanding Enthymemes in Deductive Argumentation Using Semantic Distance Measures

Anthony Hunter

Tractable Explanations for d-DNNF Classifiers

Xuanxiang Huang, Yacine Izza, Alexey Ignatiev, Martin Cooper, Nicholas Asher

Towards Explainable Action Recognition by Salient Qualitative Spatial Object Relation Chains

Hua Hua, DONGXU LI, Ruiqi Li, Peng Zhang, Jochen Renz

MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks

Nick Hoernle, Rafael Michael Karampatsis, Vaishak Belle, Kobi Gal

Conditional Abstract Dialectical Frameworks

Jesse Heyninck, Matthias Thimm, Gabriele Kern-Isberner, Tjitze Rienstra, Kenneth Skiba

BERTMap: A BERT-Based Ontology Alignment System

Yuan He, Jiaoyan Chen, Denvar Antonyrajah, Ian Horrocks

An Axiomatic Approach to Revising Preferences

Adrian Haret, Johannes Peter Wallner

Reasoning about Causal Models with Infinitely Many Variables

Joseph Y. Halpern, Spencer Peters

Sufficient Reasons for Classifier Decisions in the Presence of Domain Constraints

Niku Gorji, Sasha Rubin

Rushing and Strolling among Answer Sets – Navigation Made Easy

Johannes Klaus Fichte, Sarah Alice Gaggl, Dominik Rusovac

Linear-Time Verification of Data-Aware Dynamic Systems with Arithmetic

Paolo Felli, Marco Montali, Sarah Winkler

Axiomatization of Aggregates in Answer Set Programming

Jorge Fandinno, Zachary Hansen, Yuliya Lierler

Answering Queries with Negation over Existential Rules

Stefan Ellmauthaler, Markus Krötzsch, Stephan Mennicke

Large-Neighbourhood Search for Optimisation in Answer-Set Solving

Thomas Eiter, Tobias Geibinger, Nelson Higuera Ruiz, Nysret Musliu, Johannes Oetsch

Tractable Abstract Argumentation via Backdoor-Treewidth

Wolfgang Dvořák, Markus Hecher, Matthias König, Andre Schidler, Stefan Szeider

On the Complexity of Inductively Learning Guarded Clauses

Andrei Draghici, Georg Gottlob, Matthias Lanzinger

Machine Learning for Utility Prediction in Argument-Based Computational Persuasion

Ivan Donadello, Anthony Hunter, Stefano Teso, Mauro Dragoni

On the Computation of Necessary and Sufficient Explanations

Adnan Darwiche, Chunxi Ji

Enforcement Heuristics for Argumentation with Deep Reinforcement Learning

Dennis Craandijk, Floris Bex