papers

Publications (9)

q-fin.ST2021

Bayesian Consensus: Consensus Estimates from Miscalibrated Instruments under Heteroscedastic Noise

Chirag Nagpal, Robert E. Tillman, Prashant Reddy +1

We consider the problem of aggregating predictions or measurements from a set of human forecasters, models, sensors or other instruments which may be subject to bias or miscalibrat…

cs.LG2020

Heuristics for Link Prediction in Multiplex Networks

Robert E. Tillman, Vamsi K. Potluru, Jiahao Chen +2

Link prediction, or the inference of future or missing connections between entities, is a well-studied problem in network analysis. A multitude of heuristics exist for link predict…

q-fin.TR2019

Reinforcement Learning for Market Making in a Multi-agent Dealer Market

Sumitra Ganesh, Nelson Vadori, Mengda Xu +3

Market makers play an important role in providing liquidity to markets by continuously quoting prices at which they are willing to buy and sell, and managing inventory risk. In thi…

econ.EM2020

What can be learned from satisfaction assessments?

Naftali Cohen, Simran Lamba, Prashant Reddy

Companies survey their customers to measure their satisfaction levels with the company and its services. The received responses are crucial as they allow companies to assess their…

cs.LG2020

Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty

Nelson Vadori, Sumitra Ganesh, Prashant Reddy +1

We introduce a novel framework to account for sensitivity to rewards uncertainty in sequential decision-making problems. While risk-sensitive formulations for Markov decision proce…

cs.MA2020

Calibration of Shared Equilibria in General Sum Partially Observable Markov Games

Nelson Vadori, Sumitra Ganesh, Prashant Reddy +1

Training multi-agent systems (MAS) to achieve realistic equilibria gives us a useful tool to understand and model real-world systems. We consider a general sum partially observable…

cs.LG2021

Tradeoffs in Streaming Binary Classification under Limited Inspection Resources

Parisa Hassanzadeh, Danial Dervovic, Samuel Assefa +2

Institutions are increasingly relying on machine learning models to identify and alert on abnormal events, such as fraud, cyber attacks and system failures. These alerts often need…

cs.CL2021

DocuBot : Generating financial reports using natural language interactions

Vineeth Ravi, Selim Amrouni, Andrea Stefanucci +3

The financial services industry perpetually processes an overwhelming amount of complex data. Digital reports are often created based on tedious manual analysis as well as visualiz…

cs.AI2021

Non-Parametric Stochastic Sequential Assignment With Random Arrival Times

Danial Dervovic, Parisa Hassanzadeh, Samuel Assefa +1

We consider a problem wherein jobs arrive at random times and assume random values. Upon each job arrival, the decision-maker must decide immediately whether or not to accept the j…