1 citations · 2 across the 7 of their papers we have counts for
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Effectiveness of Curriculum Learning Depends on Reward Sparsity and Competing Optima
John J. Vastola, Ann Huang, Satpreet H. Singh +2
While animals and people tend to learn a task more quickly and reliably when they first train on simpler versions of it, curriculum learning's effectiveness in artificial settings…
Solvable models of learning to pursue a moving target
John J. Vastola, Kanaka Rajan
Agents tasked with intercepting a moving target must learn how to reach it, ideally as efficiently as possible. As observers of animal pursuit behavior have noticed, different stra…
Traversing the solution space of neural networks with Hessian Null Space Continuation
Ann Huang, Mitchell Ostrow, Zhouyang Lu +3
On a single task, deep networks can learn many solutions, depending on their optimizer, training data, architecture, and hyperparameters. Many of these solutions are mode-connected…
Implications of hierarchical Markov models of behavior: on irreversibility, predictability, and dimensionality
John J. Vastola, Kanaka Rajan
The maturation of quantitative tools for studying the high-level structure of animal behavior, and especially tools which represent spontaneous behavior as a sequence of stereotype…
A dimensional R2 regression metric
Jaesung Yoo, Stefan Lemke, Jian Zhong Guo +2
R2 score is the standard metric for evaluating regression tasks, offering a normalized magnitude-agnostic measure of accuracy that captures variance. However, R2 has three key limi…