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ORCIDDhagash Mehta
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- affiliation: University of Notre Dame, USA
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2020 – today
- 2024
[c21]Guanchao Feng, Dhruv Desai, Stefano Pasquali, Dhagash Mehta:
Open Set Recognition for Random Forest. ICAIF 2024: 45-53- [c20]Nathalia M. Castellanos, Sebastian Frank, Dhruv Desai, Stefano Pasquali, Dhagash Mehta:
Can an unsupervised clustering algorithm reproduce a categorization system? ICAIF 2024: 213-221 - [c19]Joshua Rosaler, Dhruv Desai, Bhaskarjit Sarmah, Dimitrios Vamvourellis, Deran Onay, Stefano Pasquali, Dhagash Mehta:
Enhanced Local Explainability and Trust Scores with Random Forest Proximities. ICAIF 2024: 521-529 - [c18]Bhaskarjit Sarmah, Dhagash Mehta, Benika Hall, Rohan Rao, Sunil Patel, Stefano Pasquali:
HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction. ICAIF 2024: 608-616 - [c17]Preetha Saha, Jasmine Lyu, Dhruv Desai, Rishab Chauhan, Jerinsh Jeyapaulraj, Peter Chu, Philip Sommer, Dhagash Mehta:
Machine Learning-based Relative Valuation of Municipal Bonds. ICAIF 2024: 634-642 - [c16]Mingshu Li, Bhaskarjit Sarmah, Dhruv Desai, Joshua Rosaler, Snigdha Bhagat, Philip Sommer, Dhagash Mehta:
Quantile Regression using Random Forest Proximities. ICAIF 2024: 728-736 - [c15]Eren Kurshan, Dhagash Mehta, Tucker Balch:
AI versus AI in Financial Crimes & Detection: GenAI Crime Waves to Co-Evolutionary AI. ICAIF 2024: 745-751 - [i28]Mingshu Li, Bhaskarjit Sarmah, Dhruv Desai, Joshua Rosaler, Snigdha Bhagat, Philip Sommer, Dhagash Mehta:
Quantile Regression using Random Forest Proximities. CoRR abs/2408.02355 (2024) - [i27]Guanchao Feng, Dhruv Desai, Stefano Pasquali, Dhagash Mehta:
Open Set Recognition for Random Forest. CoRR abs/2408.02684 (2024) - [i26]Bhaskarjit Sarmah, Benika Hall, Rohan Rao, Sunil Patel, Stefano Pasquali, Dhagash Mehta:
HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction. CoRR abs/2408.04948 (2024) - [i25]Gregory Yampolsky, Dhruv Desai, Mingshu Li, Stefano Pasquali, Dhagash Mehta:
Case-based Explainability for Random Forest: Prototypes, Critics, Counter-factuals and Semi-factuals. CoRR abs/2408.06679 (2024) - [i24]Nathalia M. Castellanos, Dhruv Desai, Sebastian Frank, Stefano Pasquali, Dhagash Mehta:
Can an unsupervised clustering algorithm reproduce a categorization system? CoRR abs/2408.10340 (2024) - 2023
- [j6]Edgar A. Bernal, Jonathan D. Hauenstein, Dhagash Mehta, Margaret H. Regan
, Tingting Tang:
Machine learning the real discriminant locus. J. Symb. Comput. 115: 409-426 (2023) - [j5]Jonathan D. Hauenstein, Yang-Hui He, Ilias S. Kotsireas, Dhagash Mehta, Tingting Tang:
Special issue on Algebraic Geometry and Machine Learning. J. Symb. Comput. 118: 93-94 (2023) - [c14]Bhaskarjit Sarmah, Dhagash Mehta, Stefano Pasquali, Tianjie Zhu:
Towards reducing hallucination in extracting information from financial reports using Large Language Models. AIMLSystems 2023: 39:1-39:5 - [c13]Dhruv Desai, Ashmita Dhiman, Tushar Sharma, Deepika Sharma, Dhagash Mehta, Stefano Pasquali:
Quantifying Outlierness of Funds from their Categories using Supervised Similarity. ICAIF 2023: 655-663 - [i23]Dhruv Desai, Ashmita Dhiman, Tushar Sharma, Deepika Sharma, Dhagash Mehta, Stefano Pasquali:
Quantifying Outlierness of Funds from their Categories using Supervised Similarity. CoRR abs/2308.06882 (2023) - [i22]Bhaskarjit Sarmah, Tianjie Zhu, Dhagash Mehta, Stefano Pasquali:
Towards reducing hallucination in extracting information from financial reports using Large Language Models. CoRR abs/2310.10760 (2023) - [i21]Joshua Rosaler, Dhruv Desai, Bhaskarjit Sarmah, Dimitrios Vamvourellis, Deran Onay, Dhagash Mehta, Stefano Pasquali:
Towards Enhanced Local Explainability of Random Forests: a Proximity-Based Approach. CoRR abs/2310.12428 (2023) - 2022
- [j4]Dhagash Mehta, Tianran Chen, Tingting Tang, Jonathan D. Hauenstein:
The Loss Surface of Deep Linear Networks Viewed Through the Algebraic Geometry Lens. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5664-5680 (2022) - [c12]Dimitrios Vamvourellis, Máté Tóth, Dhruv Desai, Dhagash Mehta, Stefano Pasquali:
Learning Mutual Fund Categorization using Natural Language Processing. ICAIF 2022: 87-95 - [c11]Jerinsh Jeyapaulraj, Dhruv Desai, Dhagash Mehta, Peter Chu, Stefano Pasquali, Philip Sommer:
Supervised similarity learning for corporate bonds using Random Forest proximities. ICAIF 2022: 411-419 - 2021
- [c10]Vipul Satone, Dhruv Desai, Dhagash Mehta:
Fund2Vec: mutual funds similarity using graph learning. ICAIF 2021: 16:1-16:8 - [c9]Cynthia Pagliaro, Dhagash Mehta, Han-Tai Shiao, Shaofei Wang, Luwei Xiong:
Investor behavior modeling by analyzing financial advisor notes: a machine learning perspective. ICAIF 2021: 23:1-23:8 - [i20]Vipul Satone, Dhruv Desai, Dhagash Mehta:
Fund2Vec: Mutual Funds Similarity using Graph Learning. CoRR abs/2106.12987 (2021) - 2020
- [c8]Dhagash Mehta, Dhruv Desai, Jithin Pradeep:
Machine learning fund categorizations. ICAIF 2020: 13:1-13:8 - [i19]Dhagash Mehta, Dhruv Desai, Jithin Pradeep:
Machine Learning Fund Categorizations. CoRR abs/2006.00123 (2020) - [i18]Edgar A. Bernal, Jonathan D. Hauenstein, Dhagash Mehta, Margaret H. Regan, Tingting Tang:
Machine learning the real discriminant locus. CoRR abs/2006.14078 (2020)
2010 – 2019
- 2019
- [c7]Tianran Chen, Jakub Marecek, Dhagash Mehta, Matthew E. Niemerg:
Three Formulations of the Kuramoto Model as a System of Polynomial Equations. Allerton 2019: 810-815 - [c6]Heather A. Harrington, Dhagash Mehta, Helen M. Byrne, Jonathan D. Hauenstein:
Decomposing the Parameter Space of Biological Networks via a Numerical Discriminant Approach. MC 2019: 114-131 - 2018
- [j3]Christian Knoll, Dhagash Mehta, Tianran Chen, Franz Pernkopf:
Fixed Points of Belief Propagation - An Analysis via Polynomial Homotopy Continuation. IEEE Trans. Pattern Anal. Mach. Intell. 40(9): 2124-2136 (2018) - [j2]Tianran Chen, Robert Davis, Dhagash Mehta:
Counting Equilibria of the Kuramoto Model Using Birationally Invariant Intersection Index. SIAM J. Appl. Algebra Geom. 2(4): 489-507 (2018) - [i17]Shaunak D. Bopardikar, Dhagash Mehta, Jonathan D. Hauenstein:
Optimal Configurations in Coverage Control with Polynomial Costs. CoRR abs/1801.10285 (2018) - [i16]Dhagash Mehta, Xiaojun Zhao, Edgar A. Bernal, David J. Wales:
The Loss Surface of XOR Artificial Neural Networks. CoRR abs/1804.02411 (2018) - [i15]Dhagash Mehta, Tianran Chen, Tingting Tang, Jonathan D. Hauenstein:
The loss surface of deep linear networks viewed through the algebraic geometry lens. CoRR abs/1810.07716 (2018) - [i14]Timothy E. Wang, Jack Gu, Dhagash Mehta, Xiaojun Zhao, Edgar A. Bernal:
Towards Robust Deep Neural Networks. CoRR abs/1810.11726 (2018) - 2017
- [i13]Andrew J. Ballard, Ritankar Das, Stefano Martiniani, Dhagash Mehta, Levent Sagun, Jacob D. Stevenson, David J. Wales:
Perspective: Energy Landscapes for Machine Learning. CoRR abs/1703.07915 (2017) - [i12]Souvik Chandra, Dhagash Mehta, Aranya Chakrabortty:
Locating Power Flow Solution Space Boundaries: A Numerical Polynomial Homotopy Approach. CoRR abs/1704.04792 (2017) - 2016
- [c5]Dhagash Mehta, Daniel K. Molzahn, Konstantin S. Turitsyn:
Recent advances in computational methods for the power flow equations. ACC 2016: 1753-1765 - [c4]Dhagash Mehta:
Introduction to numerical polynomial homotopy continuation methods for the power systems practitioners. ACC 2016: 1768 - [c3]Daniel K. Molzahn, Dhagash Mehta, Matthew E. Niemerg:
Toward topologically based upper bounds on the number of power flow solutions. ACC 2016: 5927-5932 - [i11]Tianran Chen, Dhagash Mehta, Matthew E. Niemerg:
A Network Topology Dependent Upper Bound on the Number of Equilibria of the Kuramoto Model. CoRR abs/1603.05905 (2016) - [i10]Daniel K. Molzahn, Matthew E. Niemerg, Dhagash Mehta, Jonathan D. Hauenstein:
Investigating the Maximum Number of Real Solutions to the Power Flow Equations: Analysis of Lossless Four-Bus Systems. CoRR abs/1603.05908 (2016) - 2015
- [j1]Jonathan D. Hauenstein, Antonio Lerario, Erik Lundberg, Dhagash Mehta:
Experiments on the Zeros of Harmonic Polynomials Using Certified Counting. Exp. Math. 24(2): 133-141 (2015) - [c2]Souvik Chandra, Dhagash Mehta, Aranya Chakrabortty:
Exploring the impact of wind penetration on power system equilibrium using a numerical continuation approach. ACC 2015: 4339-4344 - [c1]Dhagash Mehta, Crina Grosan:
A collection of challenging optimization problems in science, engineering and economics. CEC 2015: 2697-2704 - [i9]Tianran Chen, Dhagash Mehta:
Parallel degree computation for solution space of binomial systems with an application to the master space of $\mathcal{N}=1$ gauge theories. CoRR abs/1501.02237 (2015) - [i8]Dhagash Mehta, Crina Grosan:
A Collection of Challenging Optimization Problems in Science, Engineering and Economics. CoRR abs/1504.02366 (2015) - [i7]Tianran Chen, Dhagash Mehta:
An index-resolved fixed-point homotopy and potential energy landscapes. CoRR abs/1504.06622 (2015) - [i6]Daniel K. Molzahn, Dhagash Mehta, Matthew E. Niemerg:
Toward Topologically Based Upper Bounds on the Number of Power Flow Solutions. CoRR abs/1509.09227 (2015) - [i5]Dhagash Mehta, Daniel K. Molzahn, Konstantin S. Turitsyn:
Recent Advances in Computational Methods for the Power Flow Equations. CoRR abs/1510.00073 (2015) - [i4]Tianran Chen, Dhagash Mehta:
On the Network Topology Dependent Solution Count of the Algebraic Load Flow Equations. CoRR abs/1512.04987 (2015) - 2014
- [i3]Souvik Chandra, Dhagash Mehta, Aranya Chakrabortty:
Exploring the Impact of Wind Penetration on Power System Equilibrium Using a Numerical Continuation Approach. CoRR abs/1409.7844 (2014) - [i2]Joseph Cleveland, Jeffrey Dzugan, Jonathan D. Hauenstein, Ian Haywood, Dhagash Mehta, Anthony Morse, Leonardo Robol, Taylor Schlenk:
Certified counting of roots of random univariate polynomials. CoRR abs/1412.1717 (2014) - 2010
- [i1]William Hanan, Dhagash Mehta, Guillaume Moroz, Sepanda Pouryahya:
Stability and Bifurcation Analysis of Coupled Fitzhugh-Nagumo Oscillators. CoRR abs/1001.5420 (2010)
Coauthor Index
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