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2023
A New Baseline for GreenAI: Finding the Optimal Sub-Network via Layer and Channel Pruning
Xiaoying Zhi, Varun Babbar, Pheobe Sun, Fran Silavong, Ruibo Shi, Sean Moran
API-Spector: an API-to-API Specification Recommendation Engine
Sae Young Moon, Fran Silavong, Sean Moran
2022
CIKM '22: Proceedings of the 31st ACM International Conference on Information and Knowledge Management
Xiaoying Zhi , Yash Satsangi , Sean Moran , Shaltiel Eloul
Code Librarian: A Software Package Recommendation System
Lili Tao, Alexandru-Petre Cazan, Senad Ibraimoski and Sean Moran
Topical: Learning Repository Embeddings from Source Code using Attention
Agathe Lherondelle, Yash Satsangi, Fran Silavong, Shaltiel Eloul, Sean Moran
Constrained Quantum Optimization for Extractive Summarization on a Trapped-ion Quantum Computer
Pradeep Niroula, Ruslan Shaydulin, Romina Yalovetzky, Pierre Minssen, Dylan Herman, Shaohan Hu, Marco Pistoia
CV4Code: Sourcecode Understanding via Visual Code Representations
Ruibo Shi, Lili Tao, Rohan Saphal, Fran Silavong, Sean J. Moran
Shaltiel Eloul, Fran Silavong, Sanket Kamthe, Antonios Georgiadis, Sean J. Moran
FedSyn: Synthetic Data Generation using Federated Learning
Monik Raj Behera, Sudhir Upadhyay, Suresh Shetty, Sudha Priyadarshini, Palka Patel, Ker Farn Lee
ST-FL: Style Transfer Preprocessing in Federated Learning for COVID-19 Segmentation
Antonios Georgiadis (J.P. Morgan), Varun Babbar (J.P. Morgan & University of Cambridge), Fran Silavong (J.P. Morgan), Sean Moran (J.P. Morgan), and Rob Otter (J.P. Morgan)
Proceedings of SPIE 12037, Medical Imaging 2022: Imaging Informatics for Healthcare, Research, and Applications, San Diego, CA, USA, April 2022
Farzam Toudeh-Fallah, Marco Pistoia, Yasushi Kawakura, Navid Moazzami, David H. Kramer, Robert I. Woodward, Greg Sysak, Benny John, Omar Amer, Antigoni O. Polychroniadou, Jeffrey Lyon, Suresh Shetty, Tulasi D. Movva, Sudhir Upadhyay, Monik R. Behera, Joseph A. Dolphin, Paul A. Haigh, James F. Dynes., Andrew J. Shields
Senatus: A Fast and Accurate Code-To-Code Recommendation Engine
Fran Silavong (J.P. Morgan), Sean Moran (J.P. Morgan), Antonios Georgiadis (J.P. Morgan), Rohan Saphal (J.P. Morgan), Robert Otter (J.P. Morgan)
MSR '22: Proceedings of the 19th International Conference on Mining Software Repositories, Pittsburgh, PA, USA, May 2022
2021
Improving Streaming Cryptocurrency Transaction Classification via Biased Sampling and Graph Feedback
Shaltiel Eloul (J.P. Morgan), Sean Moran (J.P. Morgan), Jacob Mendel (J.P. Morgan)
ACSAC: Annual Computer Security Applications Conference, Virtual Event, USA, December 2021
Federated Learning using Smart Contracts on Blockchains, based on Reward Driven Approach
Behera, Monik Raj, Sudhir Upadhyay, and Suresh Shetty. "Federated Learning using Smart Contracts on Blockchains, based on Reward Driven Approach." arXiv preprint arXiv:2107.10243 (2021)
NISQ-HHL: Portfolio Optimization for Near-Term Quantum Hardware
Romina Yalovetzky, Pierre Minssen, Dylan Herman, Marco Pistoia Future Lab for Applied Research and Engineering, JPMorgan Chase Bank, N.A., 2021
Federated Learning using Peer-to-peer Network for Decentralized Orchestration of Model Weights
Behera, Monik Raj; upadhyay, sudhir; Shetty, Suresh; Otter, Robert (2021): Federated Learning using Peer-to-peer Network for Decentralized Orchestration of Model Weights. TechRxiv. Preprint.
2020
Behera, Monik Raj; upadhyay, sudhir; Otter, Robert; Shetty, Suresh (2020): Federated Learning using Distributed Messaging with Entitlements for Anonymous Computation and Secure Delivery of Model. TechRxiv. Preprint.
Heuristics for Link Prediction in Multiplex Networks
Robert E. Tillman (J.P. Morgan), Vamsi Potluru (J.P. Morgan), Jiahao Chen (J.P. Morgan), Prashant Reddy (J.P. Morgan), Manuela Veloso (J.P. Morgan)
In Proceedings of ECAI'20, European Conference on Artificial Intelligence, Santiago de Compostela, Spain, June, 2020
Classifying and Understand Financial Data Using Graph Neural Network
Xiaoxiao Li (Yale University), Joao Saude (J.P. Morgan), Prashant Reddy (J.P. Morgan), Manuela Veloso (J.P. Morgan)
AAAI-20 Workshop on Knowledge Discovery from Unstructured Data in Financial Services, February, 2020
2019
InverseNet: Solving Inverse Problems of Multimedia Data with Splitting Networks
Qi Wei (J.P. Morgan), Kai Fan (Alibaba DAMO Academy), Wenlin Wang (Duke University), Tianhang Zheng (SUNY at Buffalo), Chakraborty Amit (Siemens Corporate Technology), Katherine Heller (Google Brain), Changyou Chen (SUNY at Buffalo), Kui Ren (Zhejiang University)
ICME’19 Regular Paper, Shanghai, China, July 2019
Towards Inverse Reinforcement Learning for Limit Order Book Dynamics
Jacobo Roa-Vicens, Cyrine Chtourou (J.P. Morgan), Angelos Filos, Yarin Gal (University of Oxford) Francisco Rul-lan, Ricardo Silva (University College London) In ICML Workshop 'AI in Finance: Applications and Infrastructure for Multi-Agent Learning’ at the 36th International Conference on Machine Learning, ICML 2019, Long Beach, CA, USA, 2019.
(arXiv:1906.04813v1 [cs.LG] 11 Jun 2019)
Model-based Reinforcement Learning for Predictions and Control for Limit Order Books
Haoran Wei (University of Delaware), Yuanbo Wang (Twitter), Lidia Mangu (J.P. Morgan), Keith Decker (University of Delaware)
NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, Vancouver, Canada, December 2019
Adversarial recovery of agent rewards from latent spaces of the limit order book
Jacobo Roa-Vicens (J.P. Morgan), Yuanbo Wang (Twitter), Virgile Mison (J.P. Morgan), Yarin Gal (University of Oxford)
NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, Vancouver, Canada, December 2019
Classifying and Understand Financial Data Using Graph Neural Network
Sumitra Ganesh (J.P. Morgan); Nelson Vadori (J.P. Morgan); Mengda Xu (J.P. Morgan); Prashant Reddy (J.P. Morgan); Manuela Veloso (J.P. Morgan)
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 (J.P. Morgan); David Byrd (Georgia Institute of Technology); Nick Petosa (Georgia Institute of Technology); Mahmoud Mahfouz (J.P. Morgan); Danial Dervovic (J.P. Morgan); Tucker Balch (J.P. Morgan)
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December, 2019
Latent Bayesian Inference for Robust Earnings Estimates
Chirag Nagpal (Carnegie Mellon University); Robert E Tillman (J.P. Morgan AI Research); Prashant Reddy (J.P. Morgan); Manuela Veloso (J.P. Morgan)
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December, 2019
On the Importance of Opponent Modeling in Auction Markets
Mahmoud Mahfouz (J.P. Morgan), Angelos Filos (J.P. Morgan), Cyrine Chtourou (J.P. Morgan), Joshua Lockhart (J.P. Morgan), Samuel Assefa (J.P. Morgan), Manuela Veloso (J.P. Morgan), Danilo Mandic (Imperial College), Tucker Balch (J.P. Morgan)
NeurIPS'19 Workshop on Robust AI in Financial Services, Vancouver, Canada, December, 2019
Joshua Lockhart (J.P. Morgan); Samuel Assefa (J.P. Morgan); Tucker Balch (J.P. Morgan); Manuela Veloso (J.P. Morgan)
ICML'19 Workshop on AI in Finance, Long Beach, CA, June, 2019
Tucker Hybinette Balch (J.P. Morgan); Mahmoud Mahfouz (J.P.Morgan); Joshua Lockhart (J.P. Morgan); Maria Hybinette (University of Georgia); David Byrd (Georgia Institute of Technology)
ICML'19 Workshop on AI in Finance, Long Beach, CA, June, 2019
Svitlana Vyetrenko (J.P. Morgan); Shaojie Xu (Georgia Institute of Technology)
ICML'19 Workshop on AI in Finance, Long Beach, CA, June, 2019
Small Memory Robust Simulation of Interactive Protocols over Oblivious Noisy Channels
Hubert Chan, Zhibin Liang (Hong Kong U.), Antigoni Polychroniadou (J.P. Morgan), Elaine Shi (Cornell)
ACM - SIAM'19 Symposium on Discrete Algorithms, San Diego, CA, January, 2019
Trading via Image Classification
Naftali Cohen (J.P. Morgan), Tucker Balch (J.P. Morgan), Manuela Veloso (J.P. Morgan)
arXiv:1907.10046 [cs.CV], October, 2019
The Effect of Visual Design in Image Classification
Naftali Cohen (J.P. Morgan), Tucker Balch (J.P. Morgan), Manuela Veloso (J.P. Morgan)
arXiv:1907.09567 [cs.CV], August, 2019
2018
Idiosyncrasies and challenges of data driven learning in electronic trading
Vangelis Bacoyannis, Vacslav Glukhov, Tom Jin, Jonathan Kochems, Doo Re Song (J.P. Morgan)
NIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services (FEAP-AI4Fin 2018), Montréal, Canada, December, 2018
Deep Hedging: Hedging Derivatives Under Generic Market Frictions Using Reinforcement Learning
Hans Buehler, Lukas Gonon, Josef Teichmann, Ben Wood, Baranidharan Mohan, Jonathan Kochems (J.P. Morgan)
NIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services (FEAP-AI4Fin 2018), Montréal, Canada, December, 2018
Sensitivity based Neural Networks Explanations
Kay Giesecke (Stanford University), Virgile Mison (J.P. Morgan), Tao Xiong (J.P. Morgan), Lidia Mangu (J.P. Morgan)
NeurIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy, Montréal, Canada, December 2018
LMVP: Video Predictor with Leaked Motion Information
Dong Wang (Duke University) , Yitong Li (Duke University) , Wei Cao (Tsinghua University) , Liqun Chen (Duke University) , Qi Wei (J.P. Morgan), Lawrence Carin (Duke University)
NeurIPS'18 Workshop on Modeling and Decision-Making in the Spatiotemporal Domain, Montréal, Canada, December 2018
2017
An Inner-loop Free Solution to Inverse Problems using Deep Neural Networks
Qi Wei (J.P. Morgan), Kai Fan, Lawrence Carin, Katherine A. Heller (Duke University)
NIPS'17 Regular Paper, Long Beach, CA, December 2017
*Equal contribution by the authors
The [papers/presentations] on this page were prepared for informational purposes by various [technology and engineering] groups within JPMorgan Chase & Co. and its affiliates (“J.P. Morgan”), and is not a product of the Research Department of J.P. Morgan. J.P. 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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