activity
20122024
most citedFormalization of a Stochastic Approximation Theorem

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IT2024

Breaking through the classical Shannon entropy limit: A new frontier through logical semantics

Luis A. Lastras, Barry M. Trager, Jonathan Lenchner +4

Information theory has provided foundations for the theories of several application areas critical for modern society, including communications, computer storage, and AI. A key asp…

cs.PL2023★ 1 cited

Transformer Models for Type Inference in the Simply Typed Lambda Calculus: A Case Study in Deep Learning for Code

Brando Miranda, Avi Shinnar, Vasily Pestun +1

Despite a growing body of work at the intersection of deep learning and formal languages, there has been relatively little systematic exploration of transformer models for reasonin…

cs.IT2023

Towards a Unification of Logic and Information Theory

Luis A. Lastras, Barry Trager, Jonathan Lenchner +5

Today, the vast majority of the world's digital information is represented using the fundamental assumption, introduced by Claude Shannon in 1948, that ``...the semantic aspects of…

cs.LO2022★ 1 cited

Formalization of a Stochastic Approximation Theorem

Koundinya Vajjha, Barry Trager, Avraham Shinnar +1

Stochastic approximation algorithms are iterative procedures which are used to approximate a target value in an environment where the target is unknown and direct observations are…

cs.AI2020

CertRL: Formalizing Convergence Proofs for Value and Policy Iteration in Coq

Koundinya Vajjha, Avraham Shinnar, Vasily Pestun +2

Reinforcement learning algorithms solve sequential decision-making problems in probabilistic environments by optimizing for long-term reward. The desire to use reinforcement learni…

math.AG2012

Ideals of curves given by points

E. Fortuna, P. Gianni, B. Trager

Let C be an irreducible projective curve of degree d in Pn(K), where K is an algebraically closed field, and let I be the associated homogeneous prime ideal. We wish to compute gen…