Julius Lauw

Publication Activity (10 Years)

Years Active: 2019-2020
Publications (10 Years): 9

Top Topics

Bias Variance Decomposition

Jensen Shannon Divergence

Theoretic Framework

Top Venues

Australasian Conference on Artificial Intelligence

ICAART (Revised Selected Papers)

Publications

Pedro Sandoval Segura, Julius Lauw, Daniel Bashir, Kinjal Shah, Sonia Sehra, Dominique Macias, George D. Montañez
The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity. ICAART (2) (2020)
Daniel Bashir, George D. Montañez, Sonia Sehra, Pedro Sandoval Segura, Julius Lauw
An Information-Theoretic Perspective on Overfitting and Underfitting. Australasian Conference on Artificial Intelligence (2020)
George D. Montañez, Daniel Bashir, Julius Lauw
Trading Bias for Expressivity in Artificial Learning. ICAART (Revised Selected Papers) (2020)
Daniel Bashir, George D. Montañez, Sonia Sehra, Pedro Sandoval Segura, Julius Lauw
An Information-Theoretic Perspective on Overfitting and Underfitting. CoRR (2020)
Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti, George D. Montañez
The Bias-Expressivity Trade-off. ICAART (2) (2020)
Pedro Sandoval Segura, Julius Lauw, Daniel Bashir, Kinjal Shah, Sonia Sehra, Dominique Macias, George D. Montañez
The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity. CoRR (2019)
George D. Montañez, Jonathan Hayase, Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti
The Futility of Bias-Free Learning and Search. CoRR (2019)
Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti, George D. Montañez
The Bias-Expressivity Trade-off. CoRR (2019)
George D. Montañez, Jonathan Hayase, Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti
The Futility of Bias-Free Learning and Search. Australasian Conference on Artificial Intelligence (2019)