AAAI

DocuBot : Generating financial reports using natural language interactions

Vineeth Ravi, Selim Amrouni, Andrea Stefanucci, Armineh Nourbakhsh, Prashant Reddy, Manuela Veloso

Comments Accepted at :- AAAI 2021 Workshop on Content Authoring and Design (CAD21) and NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy

Conversational Neuro-Symbolic Commonsense Reasoning

Forough Arabshahi, Jennifer Lee, Mikayla Gawarecki, Kathryn Mazaitis, Amos Azaria, Tom Mitchell

Comments Appearing in the 35th AAAI international Conference on Artificial Intelligence, 2021

Hybrid Information-driven Multi-agent Reinforcement Learning

William A. Dawson, Ruben Glatt, Edward Rusu, Braden C. Soper, Ryan A. Goldhahn

Comments Published at Workshop on Challenges and Opportunities for Multi-Agent Reinforcement Learning (COMARL AAAI 2021). This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. Lawrence Livermore National Security, LLC through the support of LDRD 20-SI-005. LLNL-CONF-816423

About Face: A Survey of Facial Recognition Evaluation

Inioluwa Deborah Raji, Genevieve Fried

Comments Presented at AAAI 2020 Workshop on AI Evaluation

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan

Comments Accepted in AAAI 2021

Commonsense Knowledge Mining from Term Definitions

Zhicheng Liang, Deborah L. McGuinness

Comments In the Commonsense Knowledge Graphs (CSKGs) Workshop of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021)

Deep Deterministic Information Bottleneck with Matrix-based Entropy Functional

Xi Yu, Shujian Yu, Jose C. Principe

Comments Accepted at ICASSP-21. Code available at https://github.com/yuxi120407/DIB. Extended version of the suppelementary material in "Measuring the Dependence with Matrix-based Entropy Functional", AAAI-21, arXiv:2101.10160

Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting

Longyuan Li, Jihai Zhang, Junchi Yan, Yaohui Jin, Yunhao Zhang, Yanjie Duan, Guangjian Tian

Comments Accepted by AAAI 2021 conference

Efficient CNN Building Blocks for Encrypted Data

Nayna Jain, Karthik Nandakumar, Nalini Ratha, Sharath Pankanti, Uttam Kumar

Comments The Second AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-21)

Fake it Till You Make it: Self-Supervised Semantic Shifts for Monolingual Word Embedding Tasks

Maurício Gruppi, Sibel Adalı, Pin-Yu Chen

Comments Published at AAAI-2021

MUSE: Multi-Scale Temporal Features Evolution for Knowledge Tracing

Chengwei Zhang, Yangzhou Jiang, Wei Zhang, Chengyu Gu

Comments the AAAI-2021 workshop on Imagining Post-COVID Education with AI

Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models

Ruiyuan Wu, Anna Scaglione, Hoi-To Wai, Nurullah Karakoc, Kari Hreinsson, Wing-Kin Ma

Comments 31 pages, 5 figures. Codes available at this url {https://github.com/REIYANG/FedBCD}. To appear in AAAI 2021

Efficient Certification of Spatial Robustness

Anian Ruoss, Maximilian Baader, Mislav Balunović, Martin Vechev

Comments Conference Paper at AAAI 2021

On the Tractability of SHAP Explanations

Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu

Comments Proceedings of the 35th AAAI Conference on Artificial Intelligence

Knowledge-Enhanced Top-K Recommendation in Poincaré Ball

Chen Ma, Liheng Ma, Yingxue Zhang, Haolun Wu, Xue Liu, Mark Coates

Comments Accepted by the 35th AAAI Conference on Artificial Intelligence (AAAI 2021)

A Graph-based Relevance Matching Model for Ad-hoc Retrieval

Yufeng Zhang, Jinghao Zhang, Zeyu Cui, Shu Wu, Liang Wang

Comments To appear at AAAI 2021

Dopamine: Differentially Private Federated Learning on Medical Data

Mohammad Malekzadeh, Burak Hasircioglu, Nitish Mital, Kunal Katarya, Mehmet Emre Ozfatura, Deniz Gündüz

Comments The Second AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-21)

Learning Abstract Task Representations

Mikhail M. Meskhi, Adriano Rivolli, Rafael G. Mantovani, Ricardo Vilalta

Journal ref AAAI Workshop on Meta-Learning 2021

Winning Lottery Tickets in Deep Generative Models

Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi

Comments Published at AAAI 2021

S++: A Fast and Deployable Secure-Computation Framework for Privacy-Preserving Neural Network Training

Prashanthi Ramachandran, Shivam Agarwal, Arup Mondal, Aastha Shah, Debayan Gupta

Comments Appeared at the Second AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-21). (7 pages, technical paper.)

Overestimation learning with guarantees

Adrien Gauffriau, François Malgouyres, Mélanie Ducoffe

Journal ref AAAI-21, workshop on safeAI, Feb 2021, Valence (Virtual), Spain

Knowledge-driven Natural Language Understanding of English Text and its Applications

Kinjal Basu, Sarat Varanasi, Farhad Shakerin, Joaquin Arias, Gopal Gupta

Comments Preprint. Accepted by the 35th AAAI Conference (AAAI-21) Main Tracks

Neural Sentence Ordering Based on Constraint Graphs

Yutao Zhu, Kun Zhou, Jian-Yun Nie, Shengchao Liu, Zhicheng Dou

Comments AAAI 2021 Camera Ready

Scheduled Sampling in Vision-Language Pretraining with Decoupled Encoder-Decoder Network

Yehao Li, Yingwei Pan, Ting Yao, Jingwen Chen, Tao Mei

Comments AAAI 2021; Code is publicly available at: https://github.com/YehLi/TDEN

TSQA: Tabular Scenario Based Question Answering

Xiao Li, Yawei Sun, Gong Cheng

Comments 9 pages, accepted to AAAI 2021

Fake News Detection System using XLNet model with Topic Distributions: CONSTRAINT@AAAI2021 Shared Task

Akansha Gautam, Venktesh V, Sarah Masud

Comments Accepted at CONSTRAINT@AAAI2021 Shared Task for the CONSTRAINT workshop, collocated with AAAI 2021

An Empirical Study of Cross-Lingual Transferability in Generative Dialogue State Tracker

Yen-Ting Lin, Yun-Nung Chen

Comments DSTC9 Workshop - AAAI

On the Interpretability of Deep Learning Based Models for Knowledge Tracing

Xinyi Ding, Eric C. Larson

Journal ref AAAI 2021 workshop

Accuracy and Privacy Evaluations of Collaborative Data Analysis

Akira Imakura, Anna Bogdanova, Takaya Yamazoe, Kazumasa Omote, Tetsuya Sakurai

Comments 16 pages; 2 figures; 1 table

Journal ref To be presented at The Second AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-21) (2021)

Intelligent Frame Selection as a Privacy-Friendlier Alternative to Face Recognition

Mattijs Baert, Sam Leroux, Pieter Simoens

Comments accepted for AAAI 2021 Workshop on Privacy-Preserving Artificial Intelligence (PPAI-21)