JPMorgan Chase & Co.

research

∙ 11/05/2021

DeSkew-LSH based Code-to-Code Recommendation Engine

Machine learning on source code (MLOnCode) is a popular research field t...

Fran Silavong, et al. ∙

research

∙ 12/09/2019

Grouped sparse projection

As evident from deep learning, very large models bring improvements in t...

Nicolas Gillis, et al. ∙

research

∙ 09/19/2021

A Framework for Institutional Risk Identification using Knowledge Graphs and Automated News Profiling

Organizations around the world face an array of risks impacting their op...

Mahmoud Mahfouz, et al. ∙

research

∙ 10/31/2022

WHEN FLUE MEETS FLANG: Benchmarks and Large Pre-trained Language Model for Financial Domain

Pre-trained language models have shown impressive performance on a varie...

Raj Sanjay Shah, et al. ∙

research

∙ 08/19/2022

Topical: Learning Repository Embeddings from Source Code using Attention

Machine learning on source code (MLOnCode) promises to transform how sof...

Agathe Lherondelle, et al. ∙

research

∙ 08/04/2022

Differentially Private Counterfactuals via Functional Mechanism

Counterfactual, serving as one emerging type of model explanation, has a...

Fan Yang, et al. ∙

research

∙ 12/09/2019

Adversarial recovery of agent rewards from latent spaces of the limit order book

Inverse reinforcement learning has proved its ability to explain state-a...

Jacobo Roa-Vicens, et al. ∙

research

∙ 01/30/2020

Adversarial Code Learning for Image Generation

We introduce the "adversarial code learning" (ACL) module that improves ...

Jiangbo Yuan, et al. ∙

research

∙ 08/11/2021

Seven challenges for harmonizing explainability requirements

Regulators have signalled an interest in adopting explainable AI(XAI) te...

Jiahao Chen, et al. ∙

research

∙ 08/11/2021

Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in Practice

We review practical challenges in building and deploying ethical AI at t...

Jiahao Chen, et al. ∙

research

∙ 10/05/2021

SeanNet: Semantic Understanding Network for Localization Under Object Dynamics

We aim for domestic robots to operate indoor for long-term service. Unde...

Xiao Li, et al. ∙

research

∙ 12/03/2021

Efficient Calibration of Multi-Agent Market Simulators from Time Series with Bayesian Optimization

Multi-agent market simulation is commonly used to create an environment ...

Yuanlu Bai, et al. ∙

research

∙ 11/11/2022

pyRDDLGym: From RDDL to Gym Environments

We present pyRDDLGym, a Python framework for auto-generation of OpenAI G...

Ayal Taitler, et al. ∙

research

∙ 09/26/2022

Learning to simulate realistic limit order book markets from data as a World Agent

Multi-agent market simulators usually require careful calibration to emu...

Andrea Coletta, et al. ∙

research

∙ 10/16/2022

Biased or Limited: Modeling Sub-Rational Human Investors in Financial Markets

Multi-agent market simulation is an effective tool to investigate the im...

Penghang Liu, et al. ∙

research

∙ 11/17/2022

DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift

In electronic trading markets, limit order books (LOBs) provide informat...

Defu Cao, et al. ∙

research

∙ 10/11/2022

Code Librarian: A Software Package Recommendation System

The use of packaged libraries can significantly shorten the software dev...

Lili Tao, et al. ∙

research

∙ 09/22/2022

StyleTime: Style Transfer for Synthetic Time Series Generation

Neural style transfer is a powerful computer vision technique that can i...

Yousef El-Laham, et al. ∙

research

∙ 08/26/2022

Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions

Similarity functions measure how comparable pairs of elements are, and p...

Leonidas Tsepenekas, et al. ∙

research

∙ 11/28/2022

Inapplicable Actions Learning for Knowledge Transfer in Reinforcement Learning

Reinforcement Learning (RL) algorithms are known to scale poorly to envi...

Leo Ardon, et al. ∙

research

∙ 12/12/2022

Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe

Hawkes processes have recently risen to the forefront of tools when it c...

Renbo Zhao, et al. ∙

research

∙ 05/26/2022

Flexible Group Fairness Metrics for Survival Analysis

Algorithmic fairness is an increasingly important field concerned with d...

Raphael Sonabend, et al. ∙

research

∙ 02/20/2022

Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy

Privacy-preserving federated learning enables a population of distribute...

David Byrd, et al. ∙

research

∙ 02/08/2022

Bandit Sampling for Multiplex Networks

Graph neural networks have gained prominence due to their excellent perf...

Cenk Baykal, et al. ∙

research

∙ 12/03/2018

Sensitivity based Neural Networks Explanations

Although neural networks can achieve very high predictive performance on...

Enguerrand Horel, et al. ∙

research

∙ 10/29/2021

Profit equitably: An investigation of market maker's impact on equitable outcomes

We look at discovering the impact of market microstructure on equitabili...

Kshama Dwarakanath, et al. ∙

research

∙ 10/18/2021

Probabilistic Inference in Planning for Partially Observable Long Horizon Problems

For autonomous service robots to successfully perform long horizon tasks...

Alphonsus Adu-Bredu, et al. ∙

research

∙ 07/20/2021

Similarity metrics for Different Market Scenarios in Abides

Markov Decision Processes (MDPs) are an effective way to formally descri...

Diego Pino, et al. ∙

research

∙ 04/07/2020

Model-Agnostic Characterization of Fairness Trade-offs

There exist several inherent trade-offs in designing a fair model, such ...

Joon Sik Kim, et al. ∙

research

∙ 10/09/2019

Model-based Reinforcement Learning for Predictions and Control for Limit Order Books

We build a profitable electronic trading agent with Reinforcement Learni...

Haoran Wei, et al. ∙

research

∙ 09/29/2019

Explainable Clustering and Application to Wealth Management Compliance

Many applications from the financial industry successfully leverage clus...

Enguerrand Horel, et al. ∙

research

∙ 07/18/2019

An AI-based, Multi-stage detection system of banking botnets

Banking Trojans, botnets are primary drivers of financially-motivated cy...

Li Ling, et al. ∙

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