2 citations · 2 across the 3 of their papers we have counts for
4 papers
CARL: Chat Assisted Reinforcement Learning
Sanjiv Das, Harshad Khadilkar, Sukrit Mittal +2
Failure of applied Reinforcement Learning (RL) to solve a given problem predominantly stems from unaddressed specification gaps, where the intent of human experts in the problem's…
Converting Expert Deliberation into Financial Signals Through A Context-Aware NLP Pipeline
Vivek Batra, Kristin Chen, Sanjiv Das +6
We introduce the CDSP (context-conditional deliberation signal pipeline), converting an investment committee's meeting transcripts into structured predictive features. CDSP segment…
A Meta Reinforcement Learning Approach to Goals-Based Wealth Management
Sanjiv R. Das, Harshad Khadilkar, Sukrit Mittal +3
Applying concepts related to zero-shot meta-learning and pre-training of foundation models, we develop a meta reinforcement learning approach (denoted MetaRL) that is pre-trained o…
Enhanced Innovized Repair Operator for Evolutionary Multi- and Many-objective Optimization
Sukrit Mittal, Dhish Kumar Saxena, Kalyanmoy Deb +1
"Innovization" is a task of learning common relationships among some or all of the Pareto-optimal (PO) solutions in multi- and many-objective optimization problems. Recent studies…