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Jivitesh Sharma

4 accepted papers

2025

Generalized Convergence Analysis of Tsetlin Automaton Based Algorithms: A Probabilistic Approach to Concept Learning

Mohamed-Bachir Belaid, Jivitesh Sharma, Lei Jiao, Ole-Christoffer Granmo, Per-Arne Andersen, Anis Yazidi
AAAI 2025technical

Tsetlin Machines (TMs) have garnered increasing interest for their ability to learn concepts via propositional formulas and their proven efficiency across various application domains. Despite this, the convergence proof for the TMs, particularly for the AND operator (conjunction of literals), in the…

Cited by 0Source ↗PDF ↗code ↗Scholar ↗
2023

Building Concise Logical Patterns by Constraining Tsetlin Machine Clause Size

K. Darshana Abeyrathna, Ahmed A. O. Abouzeid, Bimal Bhattarai, Charul Giri, Sondre Glimsdal, Ole-Christoffer Granmo +5
IJCAI 2023poster

Tsetlin Machine (TM) is a logic-based machine learning approach with the crucial advantages of being transparent and hardware-friendly. While TMs match or surpass deep learning accuracy for an increasing number of applications, large clause pools tend to produce clauses with many literals (long clau…

Cited by 19Source ↗PDF ↗Scholar ↗
2023

Drop Clause: Enhancing Performance, Robustness and Pattern Recognition Capabilities of the Tsetlin Machine

Jivitesh Sharma, Rohan Yadav, Ole-Christoffer Granmo, Lei Jiao
AAAI 2023technical

Logic-based machine learning has the crucial advantage of transparency. However, despite significant recent progress, further research is needed to close the accuracy gap between logic-based architectures and deep neural network ones. This paper introduces a novel variant of the Tsetlin machine (TM)…

Cited by 20Source ↗PDF ↗Scholar ↗
2022

Tsetlin Machine for Solving Contextual Bandit Problems

Raihan Seraj, Jivitesh Sharma, Ole-Christoffer Granmo
NeurIPS 2022accept

This paper introduces an interpretable contextual bandit algorithm using Tsetlin Machines, which solves complex pattern recognition tasks using propositional (Boolean) logic. The proposed bandit learning algorithm relies on straightforward bit manipulation, thus simplifying computation and interpre…

Cited by 16Source ↗PDF ↗code ↗Scholar ↗