Search Results for author: Dhagash Mehta

Found 10 papers, 0 papers with code

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.

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 Recommendation Systems

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.

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.

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.

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.

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.

Cannot find the paper you are looking for? You can Submit a new open access paper.