Edward Moroshko

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 18

Top Topics

Linear Classification

Document Summarization

Top Venues

Publications

Itay Evron, Edward Moroshko, Gon Buzaglo, Maroun Khriesh, Badea Marjieh, Nathan Srebro, Daniel Soudry
Continual Learning in Linear Classification on Separable Data. ICML (2023)
Itay Evron, Edward Moroshko, Gon Buzaglo, Maroun Khriesh, Badea Marjieh, Nathan Srebro, Daniel Soudry
Continual Learning in Linear Classification on Separable Data. CoRR (2023)
Mark Kozdoba, Edward Moroshko, Shie Mannor, Yacov Crammer
Finite Sample Analysis Of Dynamic Regression Parameter Learning. NeurIPS (2022)
Itay Evron, Edward Moroshko, Rachel Ward, Nathan Srebro, Daniel Soudry
How catastrophic can catastrophic forgetting be in linear regression? COLT (2022)
Itay Evron, Edward Moroshko, Rachel Ward, Nati Srebro, Daniel Soudry
How catastrophic can catastrophic forgetting be in linear regression? CoRR (2022)
Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E. Woodworth, Nathan Srebro, Amir Globerson, Daniel Soudry
On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent. CoRR (2021)
Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E. Woodworth, Nathan Srebro, Amir Globerson, Daniel Soudry
On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent. ICML (2021)
Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro
Kernel and Rich Regimes in Overparametrized Models. CoRR (2020)
Edward Moroshko, Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Nati Srebro, Daniel Soudry
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy. NeurIPS (2020)
Edward Moroshko, Suriya Gunasekar, Blake E. Woodworth, Jason D. Lee, Nathan Srebro, Daniel Soudry
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy. CoRR (2020)
Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro
Kernel and Rich Regimes in Overparametrized Models. COLT (2020)
Edward Moroshko, Guy Feigenblat, Haggai Roitman, David Konopnicki
An Editorial Network for Enhanced Document Summarization. CoRR (2019)
Mark Kozdoba, Edward Moroshko, Shie Mannor, Koby Crammer
Variance Estimation For Online Regression via Spectrum Thresholding. CoRR (2019)
Itay Evron, Edward Moroshko, Koby Crammer
Efficient Loss-Based Decoding on Graphs for Extreme Classification. NeurIPS (2018)
Mark Kozdoba, Edward Moroshko, Lior Shani, Takuya Takagi, Takashi Katoh, Shie Mannor, Koby Crammer
Multi Instance Learning For Unbalanced Data. CoRR (2018)
Itay Evron, Edward Moroshko, Koby Crammer
Efficient Loss-Based Decoding On Graphs For Extreme Classification. CoRR (2018)
Edward Moroshko, Koby Crammer
Online Regression with Controlled Label Noise Rate. ECML/PKDD (2) (2017)
Edward Moroshko, Nina Vaits, Koby Crammer
Second-order non-stationary online learning for regression. J. Mach. Learn. Res. 16 (2015)
Edward Moroshko, Koby Crammer
Selective Sampling with Drift. CoRR (2014)
Edward Moroshko, Koby Crammer
Weighted last-step min-max algorithm with improved sub-logarithmic regret. Theor. Comput. Sci. 558 (2014)
Edward Moroshko, Koby Crammer
Selective Sampling with Drift. AISTATS (2014)
Edward Moroshko, Koby Crammer
A Last-Step Regression Algorithm for Non-Stationary Online Learning. AISTATS (2013)
Edward Moroshko, Koby Crammer
Weighted Last-Step Min-Max Algorithm with Improved Sub-Logarithmic Regret CoRR (2013)
Nina Vaits, Edward Moroshko, Koby Crammer
Second-Order Non-Stationary Online Learning for Regression CoRR (2013)
Edward Moroshko, Koby Crammer
A Last-Step Regression Algorithm for Non-Stationary Online Learning CoRR (2013)
Edward Moroshko, Koby Crammer
Weighted Last-Step Min-Max Algorithm with Improved Sub-logarithmic Regret. ALT (2012)