55 citations · 56 across the 6 of their papers we have counts for
6 papers
Exponential Family Discriminant Analysis: Generalizing LDA-Style Generative Classification to Non-Gaussian Models
Anish Lakkapragada
We introduce Exponential Family Discriminant Analysis (EFDA), a unified generative framework that extends classical Linear Discriminant Analysis (LDA) beyond the Gaussian setting t…
Using physics-inspired Singular Learning Theory to understand grokking & other phase transitions in modern neural networks
Anish Lakkapragada
Classical statistical inference and learning theory often fail to explain the success of modern neural networks. A key reason is that these models are non-identifiable (singular),…
Comprehensive OOD Detection Improvements
Anish Lakkapragada, Amol Khanna, Edward Raff +1
As machine learning becomes increasingly prevalent in impactful decisions, recognizing when inference data is outside the model's expected input distribution is paramount for givin…
A Novel Explanation Against Linear Neural Networks
Anish Lakkapragada
Linear Regression and neural networks are widely used to model data. Neural networks distinguish themselves from linear regression with their use of activation functions that enabl…
Mitigating Negative Transfer in Multi-Task Learning with Exponential Moving Average Loss Weighting Strategies
Anish Lakkapragada, Essam Sleiman, Saimourya Surabhi +1
Multi-Task Learning (MTL) is a growing subject of interest in deep learning, due to its ability to train models more efficiently on multiple tasks compared to using a group of conv…
Classification of Abnormal Hand Movement for Aiding in Autism Detection: Machine Learning Study
Anish Lakkapragada, Aaron Kline, Onur Cezmi Mutlu +5
A formal autism diagnosis can be an inefficient and lengthy process. Families may wait months or longer before receiving a diagnosis for their child despite evidence that earlier i…