3 citations · 7 across the 19 of their papers we have counts for
7 papers · 1 filter
A Characterization of List Language Identification in the Limit
Moses Charikar, Chirag Pabbaraju, Ambuj Tewari
We study the problem of language identification in the limit, where given a sequence of examples from a target language, the goal of the learner is to output a sequence of guesses…
A Greedy PDE Router for Blending Neural Operators and Classical Methods
Sahana Rayan, Yash Patel, Ambuj Tewari
When solving PDEs, classical numerical solvers are often computationally expensive, while machine learning methods can suffer from spectral bias, failing to capture high-frequency…
Operator Learning for Schrödinger Equation: Unitarity, Error Bounds, and Time Generalization
Yash Patel, Unique Subedi, Ambuj Tewari
We consider the problem of learning the evolution operator for the time-dependent Schrödinger equation, where the Hamiltonian may vary with time. Existing neural network-based surr…
Continuum Transformers Perform In-Context Learning by Operator Gradient Descent
Abhiti Mishra, Yash Patel, Ambuj Tewari
Transformers robustly exhibit the ability to perform in-context learning, whereby their predictive accuracy on a task can increase not by parameter updates but merely with the plac…
Offline Constrained Reinforcement Learning under Partial Data Coverage
Seokmin Ko, Ambuj Tewari, Kihyuk Hong
We study offline constrained reinforcement learning with general function approximation in discounted constrained Markov decision processes. Prior methods either require full data…
Learning to Partially Defer for Sequences
Sahana Rayan, Ambuj Tewari
In the Learning to Defer (L2D) framework, a prediction model can either make a prediction or defer it to an expert, as determined by a rejector. Current L2D methods train the rejec…
A Training-free Method for LLM Text Attribution
Tara Radvand, Mojtaba Abdolmaleki, Izak Duenyas +2
Verifying the provenance of text is increasingly important for firms, educational institutions, and online platforms as Large Language Models (LLMs) produce output that is nearly i…