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Daniel McKenzie

3 accepted papers

2026

On Logical Extrapolation for Mazes with Recurrent and Implicit Networks

AAAI 2026technical

Recent work suggests that certain neural network architectures — particularly recurrent neural networks (RNNs) and implicit neural networks (INNs) — are capable of logical extrapolation. When trained on easy instances of a task, these networks (henceforth: logical extrapolators) can generalize to mo

Cited by 0SourcePDFScholar
2022

JFB: Jacobian-Free Backpropagation for Implicit Networks

AAAI 2022technical

A promising trend in deep learning replaces traditional feedforward networks with implicit networks. Unlike traditional networks, implicit networks solve a fixed point equation to compute inferences. Solving for the fixed point varies in complexity, depending on provided data and an error tolerance.…

2021

A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization

ICML 2021spotlight

We consider the zeroth-order optimization problem in the huge-scale setting, where the dimension of the problem is so large that performing even basic vector operations on the decision variables is infeasible. In this paper, we propose a novel algorithm, coined ZO-BCD, that exhibits favorable overal…