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Artificial Intelligence Research
J.P. Morgan AI Research Publications
(all authors are from J.P. Morgan AI Research, unless otherwise noted)
Journals
Explaining Preference-driven Schedules: the EXPRES Framework (Extended Version)
Alberto Pozanco, Francesca Mosca, Parisa Zehtabi, Daniele Magazzeni, Sarit Kraus
Arxiv
Synthetic Document Generator for Annotation-free Layout Recognition
Natraj Raman, Sameena Shah, Manuela Veloso
Pattern Recognition Journal
Conferences
Counterfactual Shapley Additive Explanations
Emanuele Albini, Jason Long, Danial Dervovic, Daniele Magazzeni
FAccT, January 2022
Counterfactual Shapley Additive Explanations
Emanuele Albini, Jason Long, Danial Dervovic, Daniele Magazzeni
2022 ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT 2022), June 2022
Explaining Preference-driven Schedules: the EXPRES Framework
Alberto Pozanco, Francesca Mosca, Parisa Zehtabi, Daniele Magazzeni, Sarit Kraus
ICAPS 2022, June 2022
Assignment and Prioritization of Tasks with Uncertain Durations for Satisfying Makespans in Decentralized Execution
Sriram Gopalakrishnan, Daniel Borrajo
ICAPS 2022, June 2022
Advising Agent for Service-Providing Live-Chat Operators. [Extended Abstract]
Aviram Aviv, Yaniv Oshrat, Samuel A. Assefa, Tobi Mustapha, Daniel Borrajo, Manuela Veloso, Sarit Kraus
AAMAS 2022, May 2022
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures
Nelson Vadori, Rahul Savani, Thomas Spooner, Sumitra Ganesh
ICML, July 2022
Workshops
Towards learning to explain with concept bottleneck models: mitigating information leakage
Joshua Lockhart
ICLR Workshop on Socially Responsible Machine Learning, January 2022
CTMSTOU Driven Markets: simulated environment for regime-awareness in trading policies
Selim Amrouni, Aymeric Moulin, Tucker Balch
AAAI’22, February 2022
Global Counterfactual Explanations: Investigations, Implementations and Improvements
Dan Ley, Saumitra Mishra, Daniele Magazzeni
ICLR PAIR2Struct: Privacy Accountability, Interpretability, Robustness, Reasoning on Structured Data, April 2022
Towards learning to explain with concept bottleneck models: mitigating information leakage
Joshua Lockhart, Nicolas Marchesotti, Daniele Magazzeni, and Manuela Veloso
ICLR Workshop on Socially Responsible Machine Learning, April 2022
AI for Code Updates
Salwa Alamir, Petr Babkin, Nacho Navarro, and Sameena Shah
44th International Conference on Software Engineering: Software Engineering in Practice, May 2022
Journals
Round-Optimal Secure Multi-party Computation.
Shai Halevi, Carmit Hazay, Antigoni Polychroniadou, Muthuramakrishnan Venkitasubramaniam
Journal of Cryptology 2021
Artificial intelligence research in finance: discussion and examples
Manuela Veloso, Tucker Balch, Daniel Borrajo, Prashant Reddy, Sameena Shah
Oxford Review of Economic Policy, Volume 37, Issue 3, Autumn 2021, Pages 564–584
Conferences
Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs
Thomas Spooner, Nelson Vadori, Sumitra Ganesh
In General Proceedings of NeurIPS’21, December 2021
Improved Single-Round Secure Multiplication Using Regenerating Codes.
Mark Abspoel, Ronald Cramer, Daniel Escudero, Ivan Damgård and Chaoping Xing
ASIACRYPT’21, December 2021
Learning to Classify and Imitate Trading Agents in Continuous Double Market Auction
Mahmoud Mahfouz, Tucker Balch, Manuela Veloso, Danilo Mandic
In General Proceedings of ICAIF ’21, November 2021
Selim Amrouni, Aymeric Moulin, Jared Vann, Svitlana Vyetrenko, Tucker Balch, Manuela Veloso
In General Proceedings of ICAIF ’21, November 2021
Profit equitably: An investigation of market maker’s impact on equitable outcomes
Kshama Dwarakanath, Svitlana Vyetrenko, Tucker Balch
In General Proceedings of ICAIF ’21, November 2021
Deep Video Prediction for Time Series Forecasting
Zhen Zeng, Tucker Balch, Manuela Veloso
ICAIF’21, November 2021
Information-Theoretically Secure MPC against Mixed Dynamic Adversaries.
Ivan Damgård, Daniel Escudero and Divya Ravi
TCC’21, November 2021
Intelligent Execution through Plan Analysis
Daniel Borrajo, Manuela Veloso
In General Proceedings of
IROS'21, October 2021
Computing Opportunities to Augment Plans for Novel Replanning during Execution
Daniel Borrajo, Manuela Veloso
In General Proceedings of ICAPS’21, August 2021
Towards a fully RL-based Market Simulator
Leo Ardon, Nelson Vadori, Thomas Spooner, Mengda Xu, Jared Vann, Sumitra Ganesh
ACM International Conference on AI in Finance, October 2021
Non-parametric stochastic sequential assignment with random arrival times
Danial Dervovic, Parisa Hassanzadeh, Samuel Assefa, Prashant Reddy
In General Proceedings of IJCAI'21, August 2021
Unconditional Communication-Efficient MPC via Hall's Marriage Theorem
Vipul Goyal, Antigoni Polychroniadou, Yifan Song
CRYPTO 2021 - 41st Annual International Cryptology Conference, June 2021
ATLAS: Efficient and Scalable MPC in the Honest Majority Setting
Vipul Goyal, Hanjun Li, Rafail Ostrovsky, Antigoni Polychroniadou, Yifan Song
CRYPTO 2021 - 41st Annual International Cryptology Conference, June 2021
FinQA: A Data Set of Numerical Reasoning over Financial Data
Zhinyu Zhen, Wenhu Chen, Charese Smiley, Sameena Shah, Iana Borova, Dylan Langdom, Reema Mousa, Matt Beane, Ting-Hao Huang, Bryan Routledge, William Yang Wang
In General Proceedings of EMNLP’21, April 2021
Constant-Overhead Unconditionally Secure Multiparty Computation over Binary Fields
Antigoni Polychroniadou, Yifan Song
EUROCRYPT 2021 - 40th Annual International Conference on the Theory and Applications of Cryptographic Techniques, March 2021
Workshops
Fair when trained, unfair when deployed: fairness in performative prediction settings
Alan Mishler, Niccolo Dalmasso
NeurIPS 2021 Workshop on Algorithmic Fairness through Causality and Robustness, December 2021
Efficient Calibration of Multi-Agent Market Simulators from Time Series with Bayesian Optimization
Yuanlu Bai, Svitlana Vyetrenko, Henry Lam, Tucker Balch
NeurIPS 2021 Workshop on Optimization, December 2021
Parameterized Explanations for Investor/Company Matching
Simerjot Kaur, Ivan Brugere, Andrea Stefanucci, Armineh Nourbakhsh, Sameena Shah, Manuela Veloso
ICAIF’21 Explainable AI in Finance, November 2021
ACCO: Algebraic Computation with Comparison.
Xiaoqi Duan, Vipul Goyal, Hanjun Li, Rafail Ostrovsky, Antigoni Polychroniadou and Yifan Song
CCSW’21 (Cloud Computing Security Workshop), November 2021
Counterfactual Shapely Additive Values
Emanuele Albini, Jason Long, Danial Dervovic, Daniele Magazzeni
ICAIF’21 Workshop on Explainable AI in Finance, November 2021
A Survey on the Robustness of Feature Importance and Counterfactual Explanations
Saumitra Mishra, Sanghamitra Dutta, Jason Long, and Daniele Magazzeni
ICAIF’21 Workshop on Explainable AI in Finance, November 2021
A Planning Approach to Agile Project Management. The JIRA Planner
Salwa Alamir, Parisa Zehtabi, Rui Silva, Alberto Pozanco, Daniele Magazzeni, Daniel Borrajo, Sameena Shah, Manuela Veloso
ICAPS'21 Workshop on Planning for Financial Services, August 2021
Proving Security of Cryptographic Protocols using Automated Planning
Alberto Pozanco, Antigoni Polychroniadou, Daniele Magazzeni, Daniel Borrajo
ICAPS'21 Workshop on Planning for Financial Services, August 2021
Similarity Metrics for Transfer Learning in Financial Markets
Diego Pino González (Universidad Carlos III de Madrid) , Fernando Fernández Rebollo (Madrid), Francisco Javier García Polo (Madrid), Svitlana Vyetrenko
ICAPS'21 Workshop on Planning for Financial Services, August 2021
Tradeoffs in Sequential Binary Classification under Limited Inspection Resources
Parisa Hassanzadeh, Danial Dervovic, Samuel Assefa, Prashant Reddy, Manuela Veloso
KDD'21 Workshop on Machine Learning in Finance, August 2021
Visual Time Series Forecasting: An Image-driven Approach
Naftali Cohen, Srijan Sood, Zhen Zeng, Tucker Balch, Manuela Veloso
KDD'21, Workshop on Mining and Learning from Time Series, August 2021
Counterfactual Explanations for Arbitrary Regression Models
Thomas Spooner, Danial Dervovic, Jason Long, Jon Shepard, Jiahao Chen, Daniele Magazzeni
ICML’21 Workshop on Algorithmic Recourse, July 2021
Belief and Persuasion in Scientific Discourse on Social Media: A Study of the Covid-19 Pandemic
Salwa Alamir, Armineh Nourbakhsh, Cecilia Tilli, Sameena Shah, Manuela Veloso
AAAI’21 Workshop on AI for Behavior Change, February 2021
PayVAE: A Generative Model for Financial Transactions
Niccolo, Dalmaso, Robert Tillman, Prashant Reddy, Manuela Veloso
AAAI'21 Workshop on Knowledge Discovery from Unstructured Data in Financial Services, February 2021
DocuBot : Generating financial reports using natural language interactions
Vineeth Ravi, Sélim Amrouni, Andrea Stefanucci, Armineh Nourbakhsh, Prashant Reddy, Manuela Veloso
AAAI'21 Workshop on Content Authoring and Design, January 2021
Journals
Visual Forecasting of Time Series with Image-to-Image Regression
Naftali Cohen, Srijan Sood, Zhen Zeng, Tucker Balch, Manuela Veloso
arXiv:2011.09052 [cs.CV], November 2020
Mapping ESG Trends by Distant Supervision of Neural Language Models
Natraj Raman, Grace Bang (Bloomberg LP) and Armineh Nourbakhsh
Machine Learning and Knowledge Extraction, 2020 Dec, 2(4), pp 453-468.
Conferences
Small Memory Robust Simulation of Client-Server Interactive Protocols over Oblivious Noisy Channels
T.-H. Hubert Chan (Hong Kong University), Zhibin Liang (Hong Kong University), Antigoni Polychroniadou, Elaine Shi (Cornell University)
SODA’20, 30th ACM-SIAM Symposium on Discrete Algorithms, Salt Lake City, Utah, January 2020
Succinct Non-Interactive Secure Computation
Andrew Morgan (Cornell University), Rafael Pass (Cornell University), Antigoni Polychroniadou
EUROCRYPT’20, International Conference on the Theory and Applications of Cryptographic Techniques, May 2020
Gilad Asharov, Tucker Balch, Antigoni Polychroniadou, Manuela Veloso
AAMAS’20, International Conference on Autonomous Agents and Multi-Agent Systems, Auckland, New Zealand, May 2020
Heuristics for Link Prediction in Multiplex Networks
Robert E. Tillman, Vamsi Potluru, Jiahao Chen, Prashant Reddy, Manuela Veloso
In Proceedings of ECAI'20, European Conference on Artificial Intelligence, Santiago de Compostela, Spain, June 2020
ABIDES: Towards high-fidelity multi-agent market simulation
David Byrd (Georgia Institute of Technology); Maria Hybinette (University of Georgia); Tucker Balch
2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, June 2020
DeePlex: A GNN for Link Prediction in Multiplex Networks
Vamsi K. Potluru, Robert E. Tillman, Prashant Reddy, Manuela Veloso
SIAM - Network Science, July 2020
FACT: A Diagnostic for Group Fairness Trade-offs
Joon Sik Kim (CMU and JPMorgan Chase), Jiahao Chen, Ameet Talwalkar (CMU)
ICML 2020 (Virtual), August 2020
Daniel Borrajo, Manuela Veloso, Sameena Shah
International Conference on AI in Finance, October 2020
SURF: Improving Classifiers in Production by Learning From Busy and Noisy End Users
Joshua Lockhart, Samuel Assefa, Ayham Alajdad (J.P. Morgan Applied AI & ML), Andrew Alexander (J.P. Morgan Applied AI & ML), Tucker Balch, Manuela Veloso
ICAIF'20, International Conference on AI in Finance, October 2020
Get Real: Realism Metrics for Robust Limit Order Book Market Simulations
Svitlana Vyetrenko, David Byrd (Georgia Institute of Technology), Danial Dervovic, Tucker Balch, Mahmoud Mahfouz, Nicholas Petosa (Georgia Institute of Technology)
ICAIF’20, International Conference on AI in Finance, October 2020
Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty
Nelson Vadori, Sumitra Ganesh, Prashant Reddy, Manuela Veloso
ICAIF’20, International Conference on AI in Finance, October 2020
Trading via Image Classification
Naftali Cohen, Tucker Balch, Manuela Veloso
ICAIF’20, International Conference on AI in Finance, October 2020
SecretMatch: Inventory Matching from Fully Homomorphic Encryption
Ben Diamond, Antigoni Polychroniadou, Tucker Balch
ICAIF Conference, New York, October 2020
CryptoCredit: Securely Training Fair Models
Leo de Castro (MIT)*, Jiahao Chen, Antigoni Polychroniadou
ICAIF Conference, New York, October 2020
Eren Kursun (Columbia University), Hongda Shen (University of Alabama in Huntsville)*; Jiahao Chen
ICAIF Conference, New York, October 2020
David Byrd (Ga Tech)* & Antigoni Polychroniadou
ICAIF Conference, New York, October 2020
Generating synthetic data in finance: opportunities, challenges and pitfalls
Samuel Assefa, Danial Dervovic, Mahmoud Mahfouz , Robert Tillman , Prashant Reddy , Manuela Veloso
ICAIF Conference, New York, October 2020
Recommending Missing and Suspicious Links in Multiplex Financial Networks
Robert E Tillman, Prashant Reddy, Manuela Veloso
ICAIF Conference, New York, October 2020
Paying down metadata debt: learning the representation of concepts using topic models
Jiahao Chen & Manuela Veloso
ICAIF Conference, New York, October 2020
What can be learned from satisfaction assessments?
Naftali Cohen, Prashant Reddy, Simran Lamba
ICAIF Conference, New York, October 2020
Calibration of Shared Equilibria in General Sum Partially Observable Markov Games
Nelson Vadori, Sumitra Ganesh, Prashant Reddy, Manuela Veloso
In proceedings of NeurIPS’20, Conference on Neural Information Processing Systems, December 2020
Click here for video presentation
Workshops
Classifying and Understand Financial Data Using Graph Neural Network
Xiaoxiao Li (Yale University), Joao Saude, Prashant Reddy, Manuela Veloso
arXiv:2002.00514 [cs.SI], AAAI’20 Workshop on Knowledge Discovery from Unstructured Data in Financial Services, February 2020
Similarity metrics for transfer learning in financial markets
Daniel Pino, Javier Garcia, Fernando Fernandez, Svitlana Vyetrenko
FinPlan Workshop at ICAIF, October 2020
Goal recognition via model-based and model-free techniques
Daniel Borrajo, Sriram Gopalakrishnan (Arizona State University), Vamsi K. Potluru
ICAPS’20 Workshop in Planning for Financial Services (FinPlan), November 2020
Domain-independent generation and classification of behavior traces
Daniel Borrajo, Manuela Veloso
ICAPS’20 Workshop in Planning for Financial Services (FinPlan), November 2020
Provable Multi-Objective Reinforcement Learning with Generative Models
Dongruo Zhou (USC), Jiahao Chen, Quanquan Gu (USC)
NeurIPS Workshop on Challenges of Real-World Reinforcement Learning, December 2020
Journals
Fund asset interference using machine learning methods: what’s in that portfolio?
David Byrd (Georgia Institute of Technology), Tucker Balch
Journal of Financial Data Science, July 2019
The Effect of Visual Design in Image Classification
Naftali Cohen, Tucker Balch, Manuela Veloso
arXiv:1907.09567 [cs.CV], August 2019
Conferences
Small Memory Robust Simulation of Interactive Protocols over Oblivious Noisy Channels
Hubert Chan, Zhibin Liang (Hong Kong University), Antigoni Polychroniadou, Elaine Shi (Cornell University)
ACM - SIAM'19 Symposium on Discrete Algorithms, San Diego, CA, January 2019
Workshops
Svitlana Vyetrenko, Shaojie Xu (Georgia Institute of Technology)
ICML'19 Workshop on AI in Finance, Long Beach, CA, June 2019
Tucker Balch, Mahmoud Mahfouz, Joshua Lockhart, Maria Hybinette (University of Georgia), David Byrd (Georgia Institute of Technology)
ICML'19 Workshop on AI in Finance, Long Beach, CA, June 2019
Joshua Lockhart, Samuel Assefa, Tucker Balch, Manuela Veloso
ICML'19 Workshop on AI in Finance, Long Beach, CA, June 2019
Multi-Agent Simulation for Pricing and Hedging in a Dealer Market
Sumitra Ganesh, Nelson Vadori*, Mengda Xu*, Hua Zheng, Prashant Reddy, Manuela Veloso
ICML'19 Workshop on AI in Finance, Long Beach, CA, June 2019
Latent Bayesian Inference for Robust Earnings Estimates
Chirag Nagpal (Carnegie Mellon University), Robert E Tillman, Prashant Reddy, Manuela Veloso
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December 2019
On the Importance of Opponent Modeling in Auction Markets
Mahmoud Mahfouz, Angelos Filos, Cyrine Chtourou, Joshua Lockhart, Samuel Assefa, Manuela Veloso, Danilo Mandic (Imperial College), Tucker Balch
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December 2019
Generating Synthetic Data in Finance: Opportunities, Challenges and Pitfalls
Samuel Assefa, Danial Dervovic, Mahmoud Mahfouz, Tucker Balch, Prashant Reddy, Manuela Veloso
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December 2019
SMPAI: Secure Multi-Party Computation for Federated Learning
Antigoni Polychroniadou, Vaikkunth Mugunthan (MIT), David Byrd (Georgia Institute of Technology), Tucker Balch
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December 2019
Towards Explaining Exchange Traded Funds' Impact on Market Volatility Using an Agent-based Model
Megan J Shearer (University of Michigan), David Byrd (Georgia Institute of Technology), Tucker Balch
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December 2019
AI pptX: Robust Continuous Learning for Document Generation with AI Insights
Vineeth Ravi, Sélim Amrouni, Andrea Stefanucci, Prashant Reddy, Manuela Veloso
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December 2019
Nick Petosa (Georgia Institute of Technology), Tucker Balch
NeurIPS’19 Deep Reinforcement Learning Workshop, December 2019
Reinforcement Learning for Market Making in a Multi-agent Dealer Market
Sumitra Ganesh, Nelson Vadori, Mengda Xu, Prashant Reddy, Manuela Veloso
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December 2019
Get Real: Realism Metrics for Robust Limit Order Book Market Simulations
Svitlana Vyetrenko, David Byrd (Georgia Institute of Technology), Nick Petosa (Georgia Institute of Technology), Mahmoud Mahfouz, Danial Dervovic, Tucker Balch
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December 2019
*Equal contribution by the authors
This [paper/presentation] was prepared for informational purposes by the [Artificial Intelligence Research] group of JPMorgan Chase & Co and its affiliates (“JP Morgan”), and is not a product of the Research Department of JP Morgan. JP Morgan makes no representation and warranty whatsoever and disclaims all liability, for the completeness, accuracy or reliability of the information contained herein. This document is not intended as investment research or investment advice, or a recommendation, offer or solicitation for the purchase or sale of any security, financial instrument, financial product or service, or to be used in any way for evaluating the merits of participating in any transaction, and shall not constitute a solicitation under any jurisdiction or to any person, if such solicitation under such jurisdiction or to such person would be unlawful.
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