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IBM Research AI at AAAI 2019

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The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI) will be held January 27 – February 1, 2019 in Honolulu, Hawaii. IBM Research AI will present dozens of technical papers and demos reflecting our recent research in three key areas: advancing AI, scaling AI, and trusting AI. We believe progressing these three areas of research is essential to develop a broader form of AI that goes beyond today’s narrow, task-specific applications to learn and reason across domains using multiple modalities, while being explainable, secure, and fair. We are also excited to announce at AAAI the launch of our new IBM Research AI Residency Program.

IBM Research AI Residency Program

The AI Residency program will provide opportunities for scientists, engineers, domain experts, and entrepreneurs to engage in innovative R&D on topics in AI with the potential to impact significant technical and real-world challenges. AI residents will work closely with IBM Research scientists to fully complete a project within the 12-month residency and generate results such as publications in top AI journals and conferences (like AAAI), development of prototypes demonstrating important new AI functionality, or fielding of working AI systems. Visit our webpage for more details on the AI Residency Program, including how to apply and our topics of focus. For more than seven decades, IBM Research has defined the future of technology. Today, we are pioneering the most promising and disruptive technologies that will transform industries and society, including the future of AI. And you can be a part of it.

What’s happening in Honolulu

Along with AAAI, IBM Research is involved with co-located conferences including the AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES), The Thirty-First Innovative Applications Conference on Artificial Intelligence (IAAI), and The 9th Symposium on Educational Advances in Artificial Intelligence (EAAI-19). IBM Research is proud to sponsor AAAI (at the platinum level) and AIES. Please see details on all our papers, demos, and workshops below, and add them to your calendar.

You can also visit the IBM Research AI booth (#3) to experience first-hand the innovative tools and resources we’re creating to help unleash the power of AI. Take our tech for a spin; have fun while exploring the concepts behind our latest AI research; or learn more about our newly launched AI Residency Program. We look forward to seeing you in Honolulu!

Accepted papers at AAAI

Determinantal Reinforcement Learning
Takayuki Osogami, Raymond Rudy

Incorporating Behavioral Constraints in Online AI Systems
Avinash Balakrishnan, Djallel Bouneffouf, Nicholas Mattei, Francesca Rossi

G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification
Bingzhe Wu, Xiaolu Zhang, Shiwan Zhao, Lingxi Xie, Caihong Zeng, Guangyu Sun, Zhihong Liu

Horizontal Pyramid Matching for Person Re-identification
Yang Fu, Yunchao Wei, Yuqian Zhou, Honghui Shi, Gao Huang, Xinchao Wang, Zhiqiang Yao, Thomas Huang

GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination
Junyuan Shang, Cao Xiao, Tengfei Ma, Hongyan Li, Jimeng Sun

Weakly Supervised Scene Parsing with Point-based Distance Metric Learning
Rui Qian, Yunchao Wei, Honghui Shi, Jiachen Li, Jiaying Liu, Thomas Huang

Temporal Anomaly Detection: Calibrating the Surprise
Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer

StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
Dongliang He, Zhichao Zhou, Chuang Gan, Fu Li, Xiao Liu, Yandong Li, Limin Wang, Shilei Wen

Kernelized Hashcode Representations for Biomedical Relation Extraction
Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo Cecchi, Shuyang Gao

TAPAS: Train-less Accuracy Predictor for Architecture Search
Roxana Istrate, Florian Scheidegger, Giovanni Mariani, Dimitrios Nikolopoulos, Costas Bekas, A. Cristiano I. Malossi

Densely Supervised Grasp Detector (DSGD)
Umar Asif, Jianbin Tang, Stefan Harrer

Outlier Aware Network Embedding for Attributed Networks
Sambaran Bandyopadhyay, Lokesh N, M Narasimha Murty

CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
Akhilan Boopathy, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

Anytime Recursive Best-First Search for Bounding Marginal MAP
Radu Marinescu, Rina Dechter, Alexander Ihler, Akihiro Kishimoto, Adi Botea

AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Blackbox
Neural Networks
Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng

Unsupervised Learning with Contrastive Latent Variable Models
Kristen Severson, Soumya Ghosh, Kenney Ng

Improving Natural Language Inference Using External Knowledge in the Science Questions Domain
Xiaoyan Wang, Pavan Kapanipathi, Ryan Musa, Mo Yu, Kartik Talamadupula, Ibrahim Abdelaziz, Maria Chang, Achille Fokoue, Bassem Makni, Nicholas Mattei, Michael J. Witbrock

Knowledge Refinement via Rule Selection
Phokion Kolaitis, Lucian Popa, Kun Qian

Learning to Teach in Cooperative Multiagent Reinforcement Learning
Shayegan Omidshafiei, Dong Ki Kim, Miao Liu, Gerald Tesauro, Matthew D. Riemer, Chris Amato, Murray Campbell, Jonathan How

Tensorial Change Analysis using Probabilistic Tensor Regression
Tsuyoshi Ide

Cogra: Concept-drift-aware Stochastic Gradient Descent for Time-series Forecasting
Kohei Miyaguchi, Hiroshi Kajino

On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters
Mark Kozdoba, Jakub Marecek, Tigran Tchrakian, Shie Mannor

Toward Fast, Automatic, Privacy-Preserving Learning of Optimal Network Resource Reservation via Simple Reservation Interface
Qiao Xiang, Haitao Yu, James Aspnes, Franck Le, Linghe Kong, Y. Richard Yang

Hybrid Reinforcement Learning with Expert State Sequences
Xiaoxiao Guo, Shiyu Chang, Mo Yu, Gerald Tesauro

Unsupervised Controllable Text Formalization
Parag Jain, Abhijit Mishra, Amar Prakash Azad, Karthik Sankaranarayanan

Dynamic Learning of Sequential Choice Bandit Problem under Marketing Fatigue
Junyu Cao, Wei Sun

Validation of Growing Knowledge Graphs by Abductive Text Evidences
Jianfeng Du, Jeff Z. Pan, Sylvia Wang, Kunxun Qi, Yuming Shen, Yu Deng

A Sequential Set Generation Method for Predicting Set-Valued Outputs
Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael J. Witbrock

Red-Black Heuristics for Planning Tasks with Conditional Effects
Michael Katz

Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
Xiangpeng Li, Jingkuan Song, Lianli Gao, Xianglong Liu, Wenbing Huang, Chuang Gan, Xiangnan He

Deep Learning for Cost-Optimal Planning: Task-Dependent Planner Selection
Silvan Sievers, Michael Katz, Shirin Sohrabi, Horst Samulowitz, Patrick Ferber

Scalable Recollections for Continual Lifelong Learning
Matthew D. Riemer, Tim Klinger, Michele Franceschini, Djallel Bouneffouf

SCNN: A General Distribution based Statistical Convolutional Neural Network with Application to Video Object Detection
Tianchen Wang, Jinjun Xiong, Xiaowei Xu, Yiyu Shi

Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems
Nghia Hoang, Minh Hoang, Bryan Kian Hsiang Low, Jonathan How

Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders
Arpan Losalka, Partha Ghosh, Michael J. Black

Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting
Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang

Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
Lijie Fan, Wenbing Huang, Chuang Gan, Junzhou Huang, Boqing Gong

Demonstrations at AAAI

A General Planning-based Framework for Goal-driven Conversation Assistant
Zhuoxuan Jiang, Jie Ma, Jingyi Lu, Guangyuan Yu, Yipeng Yu, Shaochun Li

Temporal Video Analyzer (TVAN): Efficient Temporal Video Analysis for Robust Video Description and Search
Daniel Rotman, Dror Porat, Yevgeny Burshtein, Udi Barzelay

The Rensselaer Mandarin Project—a Cognitive and Immersive Language Learning Environment
David Allen, Rahul Divekar, Jaimie Drozdal, Lilit Balagyozyan, Shuyue Zheng, Ziyi Song, Huang Zou, Jeramey Tyler, Xiangyang Mou, Rui Zhao, Helen Zhou, Jianling Yue, Jeffrey O. Kephart, Hui Su

MAi: An Intelligent Model Acquisition Interface for Interactive Specification of Dialog Agents Tathagata Chakraborti, Christian Muise, Shubham Agarwal, Luis Lastras

AAAI workshops and workshop papers

Dialog System Technology Challenge (DSTC7)
Jan 27

Reasoning for Complex Question Answering
Jan 28

Ethically Bounded AI
Francesca Rossi
Artificial Intelligence Safety (SafeAI 2019)
Jan 27, 2:00-2:45 PM

Generating Dialogue Agents via Automated Planning
Adi Botea, Christian Muise, Shubham Agarwal, Oznur Alkan, Ondrej Bajgar, Elizabeth Daly, Akihiro Kishimoto, Luis Lastras, Radu Marinescu, Josef Ondrej, Pablo Pedemonte, Miroslav Vodolan
Reasoning and Learning for Human-Machine Dialogues (DEEP-DIAL 2019)
Jan 27

Automatically Detecting Data Drift in Machine Learning Based Classifiers
Orna Raz, Marcel Zalmanovici, Aviad Zlotnick, Eitan Farchi
Engineering Dependable and Secure Machine Learning Systems
Jan 28, 9:00-10:30 AM

Defending via Strategic ML Selection
Onn Shehory, Eitan Farchi, Guy Barash
Engineering Dependable and Secure Machine Learning Systems
Jan 28, 11:00-12:30 PM

Heterogeneous Knowledge Transfer via Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning
Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Gerald Tesauro, Murray Campbell, Sami Mourad, Golnaz Habibi, Jonathan How
Reinforcement Learning in Games (RLG)
Jan 28, 11:00-12:30 PM

Accepted papers at AIES

(When) Can AI Bots Lie?
Tathagata Chakraborti, Subbarao Kambhampati

Fair Transfer Learning with Missing Protected Attributes
Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty

TED: Teaching AI to Explain its Decisions
Noel Codella, Michael Hind, Karthikeyan Natesan Ramamurthy, Murray Campbell, Amit Dhurandhar, Kush Varshney, Dennis Wei, Aleksandra Mojsilovic

Using Deceased-Donor Kidneys to Initiate Chains of Living Donor Kidney Paired Donations: Algorithm and Experimentation
Cristina Cornelio, Lucrezia Furian, Antonio Nicolo, Francesca Rossi

Accepted papers at IAAI

Automated Dispatch of Helpdesk Email Tickets: Pushing the Limits with AI
Atri Mandal, Nikhil Malhotra, Shivali Agarwal, Anupama Ray, Giriprasad Sridhara

Bootstrapping Conversational Agents with Weak Supervision
Neil Mallinar, Abhishek Shah, Rajendra Ugrani, Ayush Gupta, Manikandan Gurusankar, Tin Kam Ho, Q. Vera Liao, Yunfeng Zhang, Rachel K.E. Bellamy, Robert Yates, Christopher Desmarais, Blake McGregor

A Fast Machine Learning Workflow for Rapid Phenotype Prediction from Whole Shotgun Metagenomes
Anna Paola Carrieri, Will Rowe, Martyn Winn, Edward Pyzer-Knapp

Accepted papers at EAAI

Automatic Generation of Leveled Visual Assessments for Young Learners
Anjali Singh, Ruhi Sharma Mittal, Shubham Atreja, Mourvi Sharma, Seema Nagar, Prasenjit Dey, Mohit Jain

Khan Academy: A Social Networking and Community Q&A Perspective
Sneha Mondal, Akshay Gugnani, Renuka Sindhgatta

IBM Fellow, IBM Research

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