5 citations · 8 across the 10 of their papers we have counts for
10 papers
Rank-One Fluctuations in Averaging-Learning Dynamics
Ionel Popescu, Tushar Vaidya
We study averaging-learning dynamics without an exogenous ground truth: the reference signal is generated endogenously by the population. The dynamics combine a time-varying averag…
End-to-End PDE-Based Quantum Algorithms for Multi-Asset Option Pricing under Local and Stochastic Volatility
Nikita Guseynov, Nana Liu, Chi Seng Pun +1
Multi-asset option pricing under local- and stochastic-volatility models leads naturally to high-dimensional parabolic PDEs. We develop an end-to-end quantum PDE framework for Euro…
Anchoring and Mixed-Norm Contractions in Averaging-Learning Dynamics
Ionel Popescu, Jeven Syatriadi, Tushar Vaidya
A single informed agent can draw an arbitrarily large network to the ground truth. This is the sharpest consequence of the "Averaging plus Learning" framework studied here, where a…
Quantum Algorithms for the Pathwise Lasso
Joao F. Doriguello, Debbie Lim, Chi Seng Pun +2
We present a novel quantum high-dimensional linear regression algorithm with an -penalty based on the classical LARS (Least Angle Regression) pathwise algorithm. Similarly…
Adapter Pruning using Tropical Characterization
Rishabh Bhardwaj, Tushar Vaidya, Soujanya Poria
Adapters are widely popular parameter-efficient transfer learning approaches in natural language processing that insert trainable modules in between layers of a pre-trained languag…
Abstract Visual Reasoning: An Algebraic Approach for Solving Raven's Progressive Matrices
Jingyi Xu, Tushar Vaidya, Yufei Wu +3
We introduce algebraic machine reasoning, a new reasoning framework that is well-suited for abstract reasoning. Effectively, algebraic machine reasoning reduces the difficult proce…
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP Tasks
Rishabh Bhardwaj, Tushar Vaidya, Soujanya Poria
We propose a new approach, Knowledge Distillation using Optimal Transport (KNOT), to distill the natural language semantic knowledge from multiple teacher networks to a student net…
Broken Detailed Balance and Non-Equilibrium Dynamics in Noisy Social Learning Models
Tushar Vaidya, Thiparat Chotibut, Georgios Piliouras
We propose new Degroot-type social learning models with feedback in a continuous time, to investigate the effect of a noisy information source on consensus formation in a social ne…
Averaging plus Learning Models and Their Asymptotics
Ionel Popescu, Tushar Vaidya
We develop original models to study interacting agents in financial markets and in social networks. Within these models randomness is vital as a form of shock or news that decays w…
Learning Agents in Black-Scholes Financial Markets: Consensus Dynamics and Volatility Smiles
Tushar Vaidya, Carlos Murguia, Georgios Piliouras
Black-Scholes (BS) is the standard mathematical model for option pricing in financial markets. Option prices are calculated using an analytical formula whose main inputs are strike…