Edward Moroshko
12 papers · 2013–2026 · 7 venues · across top CS/AI venues
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Machine Learning
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gradient descent
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linear regression
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continual learning
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implicit bia
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online learning
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non-stationary learning
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kernel regime
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gradient flow
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initialization scale
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regret bound
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selective sampling
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reproducing kernel hilbert space
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catastrophic forgetting
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linear classification
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learning theory
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parameter learning
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document summarization
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Papers
Optimal L2 Regularization in High-dimensional Continual Linear Regression
ALT 2026
Continual Learning in Linear Classification on Separable Data
ICML 2023
Finite Sample Analysis Of Dynamic Regression Parameter Learning
NeurIPS 2022
How catastrophic can catastrophic forgetting be in linear regression?
COLT 2022
On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent
ICML 2021
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy
NeurIPS 2020
Kernel and Rich Regimes in Overparametrized Models
COLT 2020
An Editorial Network for Enhanced Document Summarization
EMNLP 2019
Efficient Loss-Based Decoding on Graphs for Extreme Classification
NeurIPS 2018
Second-Order Non-Stationary Online Learning for Regression
JMLR 2015
Selective Sampling with Drift
AISTATS 2014
A Last-Step Regression Algorithm for Non-Stationary Online Learning
AISTATS 2013