Search Results for author: Dhagash Mehta

Found 18 papers, 0 papers with code

Towards Enhanced Local Explainability of Random Forests: a Proximity-Based Approach

no code implementations19 Oct 2023 Joshua Rosaler, Dhruv Desai, Bhaskarjit Sarmah, Dimitrios Vamvourellis, Deran Onay, Dhagash Mehta, Stefano Pasquali

We initiate a novel approach to explain the out of sample performance of random forest (RF) models by exploiting the fact that any RF can be formulated as an adaptive weighted K nearest-neighbors model.

Towards reducing hallucination in extracting information from financial reports using Large Language Models

no code implementations16 Oct 2023 Bhaskarjit Sarmah, Tianjie Zhu, Dhagash Mehta, Stefano Pasquali

For a financial analyst, the question and answer (Q\&A) segment of the company financial report is a crucial piece of information for various analysis and investment decisions.

Hallucination Optical Character Recognition +2

Company Similarity using Large Language Models

no code implementations15 Aug 2023 Dimitrios Vamvourellis, Máté Toth, Snigdha Bhagat, Dhruv Desai, Dhagash Mehta, Stefano Pasquali

Identifying companies with similar profiles is a core task in finance with a wide range of applications in portfolio construction, asset pricing and risk attribution.

Quantifying Outlierness of Funds from their Categories using Supervised Similarity

no code implementations14 Aug 2023 Dhruv Desai, Ashmita Dhiman, Tushar Sharma, Deepika Sharma, Dhagash Mehta, Stefano Pasquali

Mutual fund categorization has become a standard tool for the investment management industry and is extensively used by allocators for portfolio construction and manager selection, as well as by fund managers for peer analysis and competitive positioning.

Management Metric Learning +1

Learning Embedded Representation of the Stock Correlation Matrix using Graph Machine Learning

no code implementations14 Jul 2022 Bhaskarjit Sarmah, Nayana Nair, Dhagash Mehta, Stefano Pasquali

In particular, the algorithm compresses the network into a lower dimensional continuous space, called an embedding, where pairs of nodes that are identified as similar by the algorithm are placed closer to each other.

BIG-bench Machine Learning Management

Learning Mutual Fund Categorization using Natural Language Processing

no code implementations11 Jul 2022 Dimitrios Vamvourellis, Mate Attila Toth, Dhruv Desai, Dhagash Mehta, Stefano Pasquali

Categorization of mutual funds or Exchange-Traded-funds (ETFs) have long served the financial analysts to perform peer analysis for various purposes starting from competitor analysis, to quantifying portfolio diversification.

Multi-class Classification

Supervised similarity learning for corporate bonds using Random Forest proximities

no code implementations10 Jul 2022 Jerinsh Jeyapaulraj, Dhruv Desai, Peter Chu, Dhagash Mehta, Stefano Pasquali, Philip Sommer

Financial literature consists of ample research on similarity and comparison of financial assets and securities such as stocks, bonds, mutual funds, etc.

Management Metric Learning

Investor Behavior Modeling by Analyzing Financial Advisor Notes: A Machine Learning Perspective

no code implementations12 Jul 2021 Cynthia Pagliaro, Dhagash Mehta, Han-Tai Shiao, Shaofei Wang, Luwei Xiong

With the help of natural language processing (NLP) we analyze an unstructured (textual) dataset of financial advisors' summary notes, taken after every investor conversation, to gain first ever insights into advisor-investor interactions.

BIG-bench Machine Learning Decision Making

Fund2Vec: Mutual Funds Similarity using Graph Learning

no code implementations24 Jun 2021 Vipul Satone, Dhruv Desai, Dhagash Mehta

Identifying similar mutual funds with respect to the underlying portfolios has found many applications in financial services ranging from fund recommender systems, competitors analysis, portfolio analytics, marketing and sales, etc.

Graph Learning Marketing +1

Machine learning the real discriminant locus

no code implementations24 Jun 2020 Edgar A. Bernal, Jonathan D. Hauenstein, Dhagash Mehta, Margaret H. Regan, Tingting Tang

This article views locating the real discriminant locus as a supervised classification problem in machine learning where the goal is to determine classification boundaries over the parameter space, with the classes being the number of real solutions.

BIG-bench Machine Learning

Machine Learning Fund Categorizations

no code implementations29 May 2020 Dhagash Mehta, Dhruv Desai, Jithin Pradeep

Given the surge in popularity of mutual funds (including exchange-traded funds (ETFs)) as a diversified financial investment, a vast variety of mutual funds from various investment management firms and diversification strategies have become available in the market.

BIG-bench Machine Learning Management +1

Towards Robust Deep Neural Networks

no code implementations27 Oct 2018 Timothy E. Wang, Yiming Gu, Dhagash Mehta, Xiaojun Zhao, Edgar A. Bernal

We investigate the topics of sensitivity and robustness in feedforward and convolutional neural networks.

Adversarial Robustness

The loss surface of deep linear networks viewed through the algebraic geometry lens

no code implementations17 Oct 2018 Dhagash Mehta, Tianran Chen, Tingting Tang, Jonathan D. Hauenstein

By using the viewpoint of modern computational algebraic geometry, we explore properties of the optimization landscapes of the deep linear neural network models.

The Loss Surface of XOR Artificial Neural Networks

no code implementations6 Apr 2018 Dhagash Mehta, Xiaojun Zhao, Edgar A. Bernal, David J. Wales

Training an artificial neural network involves an optimization process over the landscape defined by the cost (loss) as a function of the network parameters.

Perspective: Energy Landscapes for Machine Learning

no code implementations23 Mar 2017 Andrew J. Ballard, Ritankar Das, Stefano Martiniani, Dhagash Mehta, Levent Sagun, Jacob D. Stevenson, David J. Wales

Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences.

BIG-bench Machine Learning

Fixed Points of Belief Propagation -- An Analysis via Polynomial Homotopy Continuation

no code implementations20 May 2016 Christian Knoll, Franz Pernkopf, Dhagash Mehta, Tianran Chen

Moreover, we show that this fixed point gives a good approximation, and the NPHC method is able to obtain this fixed point.

A Collection of Challenging Optimization Problems in Science, Engineering and Economics

no code implementations9 Apr 2015 Dhagash Mehta, Crina Grosan

Function optimization and finding simultaneous solutions of a system of nonlinear equations (SNE) are two closely related and important optimization problems.


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