no code implementations • NAACL (DaSH) 2021 • Natraj Raman, Sameena Shah, Tucker Balch, Manuela Veloso
Information visualization is critical to analytical reasoning and knowledge discovery.
no code implementations • 20 Mar 2024 • Tucker Balch, Vamsi K. Potluru, Deepak Paramanand, Manuela Veloso
In addition to the benefits it provides, such as improved financial modeling and better testing procedures, it poses privacy risks as well.
no code implementations • 17 Mar 2024 • Zhen Zeng, Rachneet Kaur, Suchetha Siddagangappa, Tucker Balch, Manuela Veloso
Time series forecasting plays a crucial role in decision-making across various domains, but it presents significant challenges.
no code implementations • 13 Feb 2024 • Andrea Coletta, Kshama Dwarakanath, Penghang Liu, Svitlana Vyetrenko, Tucker Balch
We make an assumption that LLMs can be used as implicit computational models of humans, and propose a framework to use synthetic demonstrations derived from LLMs to model subrational behaviors that are characteristic of humans (e. g., myopic behavior or preference for risk aversion).
no code implementations • 1 Jan 2024 • Yinan Cheng, Chi-Hua Wang, Vamsi K. Potluru, Tucker Balch, Guang Cheng
Devising procedures for downstream task-oriented generative model selections is an unresolved problem of practical importance.
no code implementations • 29 Dec 2023 • Vamsi K. Potluru, Daniel Borrajo, Andrea Coletta, Niccolò Dalmasso, Yousef El-Laham, Elizabeth Fons, Mohsen Ghassemi, Sriram Gopalakrishnan, Vikesh Gosai, Eleonora Kreačić, Ganapathy Mani, Saheed Obitayo, Deepak Paramanand, Natraj Raman, Mikhail Solonin, Srijan Sood, Svitlana Vyetrenko, Haibei Zhu, Manuela Veloso, Tucker Balch
Synthetic data has made tremendous strides in various commercial settings including finance, healthcare, and virtual reality.
no code implementations • 9 Nov 2023 • Zikai Xiong, Niccolò Dalmasso, Shubham Sharma, Freddy Lecue, Daniele Magazzeni, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
In this work, we present fair Wasserstein coresets (FWC), a novel coreset approach which generates fair synthetic representative samples along with sample-level weights to be used in downstream learning tasks.
no code implementations • 31 Oct 2023 • Zikai Xiong, Niccolò Dalmasso, Alan Mishler, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
FairWASP can therefore be used to construct datasets which can be fed into any classification method, not just methods which accept sample weights.
no code implementations • 28 Sep 2023 • Tom Bamford, Andrea Coletta, Elizabeth Fons, Sriram Gopalakrishnan, Svitlana Vyetrenko, Tucker Balch, Manuela Veloso
Moreover, the required storage, computational time, and retrieval complexity to search in the time-series space are often non-trivial.
no code implementations • 4 Sep 2023 • Song Wei, Andrea Coletta, Svitlana Vyetrenko, Tucker Balch
To adapt to any environment with interactive sequential decision making agents, INTAGS formulates the simulator as a stochastic policy in reinforcement learning.
no code implementations • 22 Aug 2023 • Saba Rahimi, Tucker Balch, Manuela Veloso
The GPT-3 model achieved a 96% passing score on a set of 50 sample driving knowledge test questions.
no code implementations • 19 Jun 2023 • Eleonora Kreačić, Navid Nouri, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
Creation of a synthetic dataset that faithfully represents the data distribution and simultaneously preserves privacy is a major research challenge.
no code implementations • 11 Apr 2023 • Zhen Zeng, Rachneet Kaur, Suchetha Siddagangappa, Saba Rahimi, Tucker Balch, Manuela Veloso
In our experiments, we demonstrated the success of the proposed method in comparison to commonly adopted statistical and deep learning methods on forecasting intraday stock price change of S&P 500 constituents.
no code implementations • 23 Feb 2023 • Andrea Coletta, Svitlana Vyetrenko, Tucker Balch
Finally, by clustering the explanations we show that we are able to identify different agent policies and group observations accordingly.
no code implementations • 12 Dec 2022 • Renbo Zhao, Niccolò Dalmasso, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
Hawkes processes have recently risen to the forefront of tools when it comes to modeling and generating sequential events data.
no code implementations • 16 Oct 2022 • Penghang Liu, Kshama Dwarakanath, Svitlana S Vyetrenko, Tucker Balch
We evaluate the behavior of sub-rational human investors using hand-crafted market scenarios and SHAP value analysis, showing that our model accurately reproduces the observations in the previous studies and reveals insights of the driving factors of human behavior.
no code implementations • 13 Oct 2022 • Nelson Vadori, Leo Ardon, Sumitra Ganesh, Thomas Spooner, Selim Amrouni, Jared Vann, Mengda Xu, Zeyu Zheng, Tucker Balch, Manuela Veloso
We study a game between liquidity provider and liquidity taker agents interacting in an over-the-counter market, for which the typical example is foreign exchange.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 26 Sep 2022 • Andrea Coletta, Aymeric Moulin, Svitlana Vyetrenko, Tucker Balch
Our approach proposes to learn a unique "world" agent from historical data.
no code implementations • 22 Sep 2022 • Kshama Dwarakanath, Svitlana S Vyetrenko, Tucker Balch
The goal of this work is to design a dynamic fee schedule for the marketplace that is equitable and profitable to all traders while being profitable to the marketplace at the same time (from charging fees).
no code implementations • 22 Sep 2022 • Kshama Dwarakanath, Danial Dervovic, Peyman Tavallali, Svitlana S Vyetrenko, Tucker Balch
We propose a novel group of Gaussian Process based algorithms for fast approximate optimal stopping of time series with specific applications to financial markets.
no code implementations • 16 Aug 2022 • Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru, Sameena Shah, Tucker Balch, Manuela Veloso
Online learning of Hawkes processes has received increasing attention in the last couple of years especially for modeling a network of actors.
no code implementations • 27 Jul 2022 • Mohsen Ghassemi, Eleonora Kreačić, Niccolò Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
Hawkes processes have recently gained increasing attention from the machine learning community for their versatility in modeling event sequence data.
no code implementations • 2 Feb 2022 • Selim Amrouni, Aymeric Moulin, Tucker Balch
Market regimes is a popular topic in quantitative finance even though there is little consensus on the details of how they should be defined.
no code implementations • 3 Dec 2021 • Yuanlu Bai, Henry Lam, Svitlana Vyetrenko, Tucker Balch
Multi-agent simulation is commonly used across multiple disciplines, specifically in artificial intelligence in recent years, which creates an environment for downstream machine learning or reinforcement learning tasks.
1 code implementation • 27 Oct 2021 • Selim Amrouni, Aymeric Moulin, Jared Vann, Svitlana Vyetrenko, Tucker Balch, Manuela Veloso
We introduce a general technique to wrap a DEMAS simulator into the Gym framework.
no code implementations • 25 Oct 2021 • Andrea Coletta, Matteo Prata, Michele Conti, Emanuele Mercanti, Novella Bartolini, Aymeric Moulin, Svitlana Vyetrenko, Tucker Balch
Unfortunately, this approach does not capture the market response to the experimental agents' actions.
no code implementations • 4 Oct 2021 • Mahmoud Mahfouz, Tucker Balch, Manuela Veloso, Danilo Mandic
Continuous double auctions such as the limit order book employed by exchanges are widely used in practice to match buyers and sellers of a variety of financial instruments.
no code implementations • 2 Aug 2021 • Victor Storchan, Svitlana Vyetrenko, Tucker Balch
In electronic trading markets often only the price or volume time series, that result from interaction of multiple market participants, are directly observable.
no code implementations • 2 Jul 2021 • Naftali Cohen, Srijan Sood, Zhen Zeng, Tucker Balch, Manuela Veloso
In this work, we address time-series forecasting as a computer vision task.
no code implementations • 27 May 2021 • Yuanlu Bai, Tucker Balch, Haoxian Chen, Danial Dervovic, Henry Lam, Svitlana Vyetrenko
Stochastic simulation aims to compute output performance for complex models that lack analytical tractability.
no code implementations • 24 Feb 2021 • Zhen Zeng, Tucker Balch, Manuela Veloso
In this paper, we propose to approach economic time series forecasting of multiple financial assets in a novel way via video prediction.
no code implementations • 1 Jan 2021 • Victor Storchan, Svitlana Vyetrenko, Tucker Balch
In this paper, we present SIM-GAN -- a multi-agent simulator calibration method that allows to tune simulator parameters and to support more accurate evaluations of candidate trading algorithm.
no code implementations • 18 Nov 2020 • Srijan Sood, Zhen Zeng, Naftali Cohen, Tucker Balch, Manuela Veloso
In this work, we leverage advances in deep learning to extend the field of time series forecasting to a visual setting.
no code implementations • 12 Oct 2020 • Joshua Lockhart, Samuel Assefa, Ayham Alajdad, Andrew Alexander, Tucker Balch, Manuela Veloso
We show that conventional crowdsourcing algorithms struggle in this user feedback setting, and present a new algorithm, SURF, that can cope with this non-response ambiguity.
no code implementations • 27 Apr 2020 • Joshua Lockhart, Samuel Assefa, Tucker Balch, Manuela Veloso
Document classification is ubiquitous in a business setting, but often the end users of a classifier are engaged in an ongoing feedback-retrain loop with the team that maintain it.
no code implementations • 28 Nov 2019 • Mahmoud Mahfouz, Angelos Filos, Cyrine Chtourou, Joshua Lockhart, Samuel Assefa, Manuela Veloso, Danilo Mandic, Tucker Balch
The dynamics of financial markets are driven by the interactions between participants, as well as the trading mechanisms and regulatory frameworks that govern these interactions.
1 code implementation • 29 Oct 2019 • Nick Petosa, Tucker Balch
The AlphaZero algorithm has achieved superhuman performance in two-player, deterministic, zero-sum games where perfect information of the game state is available.
2 code implementations • 23 Jul 2019 • Naftali Cohen, Tucker Balch, Manuela Veloso
The art of systematic financial trading evolved with an array of approaches, ranging from simple strategies to complex algorithms all relying, primary, on aspects of time-series analysis.
no code implementations • 22 Jul 2019 • Naftali Cohen, Tucker Balch, Manuela Veloso
In this study, we examine whether binary decisions are better to be decided based on the numeric or the visual representation of the same data.