AAAI

Towards Feature Space Adversarial Attack

Qiuling Xu, Guanhong Tao, Siyuan Cheng, Xiangyu Zhang

Comments AAAI 2021

Towards Reusable Network Components by Learning Compatible Representations

Michael Gygli, Jasper Uijlings, Vittorio Ferrari

Comments Preprint; To be presented at AAAI 2021

Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example

Serena Booth, Yilun Zhou, Ankit Shah, Julie Shah

Comments Accepted at AAAI 2021

Deep Reinforcement Learning for Active Human Pose Estimation

Erik Gärtner, Aleksis Pirinen, Cristian Sminchisescu

Comments Accepted to The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20). Submission updated to include supplementary material

Guiding Non-Autoregressive Neural Machine Translation Decoding with Reordering Information

Qiu Ran, Yankai Lin, Peng Li, Jie Zhou

Comments Accepted by AAAI 2021

Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently

Rebekka Burkholz, John Quackenbush

Comments Accepted at AAAI 2021

Learning to Sit: Synthesizing Human-Chair Interactions via Hierarchical Control

Yu-Wei Chao, Jimei Yang, Weifeng Chen, Jia Deng

Comments Accepted to AAAI 2021

Nested Named Entity Recognition with Partially-Observed TreeCRFs

Yao Fu, Chuanqi Tan, Mosha Chen, Songfang Huang, Fei Huang

Comments AAAI 2021 Camera Ready

Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games

Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian Ratliff

Comments To appear in AAAI 2021

Fair and Efficient Allocations under Lexicographic Preferences

Hadi Hosseini, Sujoy Sikdar, Rohit Vaish, Lirong Xia

Comments Full version of a paper that appears at AAAI Conference on Artificial Intelligence (AAAI) 2021

The Gap on GAP: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets

Vid Kocijan, Oana-Maria Camburu, Thomas Lukasiewicz

Comments Accepted to AAAI 2021 conference and AFCI workshop at NeurIPS 2020 conference

Journal ref AAAI 2021

Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks

Arijit Sehanobish, Neal G. Ravindra, David van Dijk

Comments To appear at AAAI'21. Previous version (v2) accepted as a spotlight talk at ICML 2020 Workshop on Graph Representation Learning and Beyond (GRL+) and recipient of best paper award for Covid-19 applications. Significant improvements over v2

Neural Analogical Matching

Maxwell Crouse, Constantine Nakos, Ibrahim Abdelaziz, Kenneth Forbus

Comments AAAI version

VSQL: Variational Shadow Quantum Learning for Classification

Guangxi Li, Zhixin Song, Xin Wang

Comments 20 pages. To appear in the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021)

Artificial Dummies for Urban Dataset Augmentation

Antonín Vobecký, David Hurych, Michal Uřičář, Patrick Pérez, Josef Šivic

Comments Accepted to AAAI 2021

*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task

Dmitry Tsarkov, Tibor Tihon, Nathan Scales, Nikola Momchev, Danila Sinopalnikov, Nathanael Schärli

Comments Accepted, AAAI-21

Learning to Check Contract Inconsistencies

Shuo Zhang, Junzhou Zhao, Pinghui Wang, Nuo Xu, Yang Yang, Yiting Liu, Yi Huang, Junlan Feng

Comments Accepted by AAAI 2021

Relation-Aware Neighborhood Matching Model for Entity Alignment

Yao Zhu, Hongzhi Liu, Zhonghai Wu, Yingpeng Du

Comments AAAI 2021

Hypothesis Disparity Regularized Mutual Information Maximization

Qicheng Lao, Xiang Jiang, Mohammad Havaei

Comments Accepted to AAAI 2021

Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision

Faeze Brahman, Vered Shwartz, Rachel Rudinger, Yejin Choi

Comments AAAI 2021

Binary Black-box Evasion Attacks Against Deep Learning-based Static Malware Detectors with Adversarial Byte-Level Language Model

Mohammadreza Ebrahimi, Ning Zhang, James Hu, Muhammad Taqi Raza, Hsinchun Chen

Comments Accepted in 35th AAAI Conference on Artificial Intelligence, Workshop on Robust, Secure, and Efficient Machine Learning (RSEML)

Journal ref AAAI Conference on Artificial Intelligence, Workshop on Robust, Secure, and Efficient Machine Learning (RSEML), February 2-9, 2021

Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search

Li-Cheng Lan, Meng-Yu Tsai, Ti-Rong Wu, I-Chen Wu, Cho-Jui Hsieh

Comments Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21)

SSD-GAN: Measuring the Realness in the Spatial and Spectral Domains

Yuanqi Chen, Ge Li, Cece Jin, Shan Liu, Thomas Li

Comments Accepted to AAAI 2021. Code: https://github.com/cyq373/SSD-GAN

Dynamic Anchor Learning for Arbitrary-Oriented Object Detection

Qi Ming, Zhiqiang Zhou, Lingjuan Miao, Hongwei Zhang, Linhao Li

Comments Accepted to AAAI 2021. The code and models are available at https://github.com/ming71/DAL

Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory

Stefanos Leonardos, Georgios Piliouras

Comments Appears in the 35th AAAI Conference on Artificial Intelligence

Knowledge-driven Data Construction for Zero-shot Evaluation in Commonsense Question Answering

Kaixin Ma, Filip Ilievski, Jonathan Francis, Yonatan Bisk, Eric Nyberg, Alessandro Oltramari

Comments AAAI 2021

Explaining Neural Matrix Factorization with Gradient Rollback

Carolin Lawrence, Timo Sztyler, Mathias Niepert

Comments 35th AAAI Conference on Artificial Intelligence, 2021. Includes Appendix

SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors

Ardavan Afshar, Kejing Yin, Sherry Yan, Cheng Qian, Joyce C. Ho, Haesun Park, Jimeng Sun

Comments Accepted by AAAI-21

Hierarchical Relational Inference

Aleksandar Stanić, Sjoerd van Steenkiste, Jürgen Schmidhuber

Comments Accepted to AAAI 2021

Understanding Catastrophic Overfitting in Single-step Adversarial Training

Hoki Kim, Woojin Lee, Jaewook Lee

Comments Accepted to AAAI 2021. Preprint