165 citations · 179 across the 11 of their papers we have counts for
11 papers
Conservative Predictions on Noisy Financial Data
Omkar Nabar, Gautam Shroff
Price movements in financial markets are well known to be very noisy. As a result, even if there are, on occasion, exploitable patterns that could be picked up by machine-learning…
Adapt and Decompose: Efficient Generalization of Text-to-SQL via Domain Adapted Least-To-Most Prompting
Aseem Arora, Shabbirhussain Bhaisaheb, Harshit Nigam +3
Cross-domain and cross-compositional generalization of Text-to-SQL semantic parsing is a challenging task. Existing Large Language Model (LLM) based solutions rely on inference-tim…
Neuro-symbolic Meta Reinforcement Learning for Trading
S I Harini, Gautam Shroff, Ashwin Srinivasan +2
We model short-duration (e.g. day) trading in financial markets as a sequential decision-making problem under uncertainty, with the added complication of continual concept-drift. W…
Minimally-Supervised Attribute Fusion for Data Lakes
Karamjit Singh, Garima Gupta, Gautam Shroff +1
Aggregate analysis, such as comparing country-wise sales versus global market share across product categories, is often complicated by the unavailability of common join attributes,…
Deep Convolutional Neural Networks for Pairwise Causality
Karamjit Singh, Garima Gupta, Lovekesh Vig +2
Discovering causal models from observational and interventional data is an important first step preceding what-if analysis or counterfactual reasoning. As has been shown before, th…
Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs
Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan +3
We investigate solving discrete optimisation problems using the estimation of distribution (EDA) approach via a novel combination of deep belief networks(DBN) and inductive logic p…