Provable Memorization via Deep Neural Networks using Sub-linear
Parameters

Provable Memorization via Deep Neural Networks using Sub-linear Parameters

26 October 2020

Sejun Park

Papers citing "Provable Memorization via Deep Neural Networks using Sub-linear Parameters"

10 / 10 papers shown

Title
Deep Kalman Filters Can Filter Blanka Hovart Anastasis Kratsios Yannick Limmer Xuwei Yang 45 1 0 31 Dec 2024
On the Complexity of Neural Computation in Superposition Micah Adler Nir Shavit 115 3 0 05 Sep 2024
Minimum width for universal approximation using ReLU networks on compact domain Namjun Kim Chanho Min Sejun Park VLM 29 10 0 19 Sep 2023
Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators? T. Kajitsuka Issei Sato 31 16 0 26 Jul 2023
Memorization Capacity of Multi-Head Attention in Transformers Sadegh Mahdavi Renjie Liao Christos Thrampoulidis 26 22 0 03 Jun 2023
Memorization Capacity of Neural Networks with Conditional Computation Erdem Koyuncu 30 4 0 20 Mar 2023
When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work Jiawei Zhang Yushun Zhang Mingyi Hong Ruoyu Sun Z. Luo 26 10 0 21 Oct 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 46 20 0 31 Jan 2022
The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training Andrea Montanari Yiqiao Zhong 47 95 0 25 Jul 2020
Benefits of depth in neural networks Matus Telgarsky 142 602 0 14 Feb 2016