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From the 1 of 1.7k papers with an AI index.

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20052025
most citedBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

24.4k citations

Showing 2021Show all

348 papers · 1 filter

cs.LG20212 cited

Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies

Paul Vicol, Luke Metz, Jascha Sohl-Dickstein

Unrolled computation graphs arise in many scenarios, including training RNNs, tuning hyperparameters through unrolled optimization, and training learned optimizers. Current approac…

cs.NI20213 cited

Energy-Proportional Data Center Network Architecture Through OS, Switch and Laser Co-design

Haiyang Han, Nikos Terzenidis, Dimitris Syrivelis +8

Optical interconnects are already the dominant technology in large-scale data center networks. However, the high optical loss of many optical components coupled with the low effici…

cs.CR20216 cited

Privacy Guarantees of BLE Contact Tracing: A Case Study on COVIDWISE

Salman Ahmed, Ya Xiao, Taejoong +5

Google and Apple jointly introduced a digital contact tracing technology and an API called "exposure notification," to help health organizations and governments with contact tracin…

cs.LG202112 cited

Information is Power: Intrinsic Control via Information Capture

Nicholas Rhinehart, Jenny Wang, Glen Berseth +4

Humans and animals explore their environment and acquire useful skills even in the absence of clear goals, exhibiting intrinsic motivation. The study of intrinsic motivation in art…

cs.LG20216 cited

Noether Networks: Meta-Learning Useful Conserved Quantities

Ferran Alet, Dylan Doblar, Allan Zhou +3

Progress in machine learning (ML) stems from a combination of data availability, computational resources, and an appropriate encoding of inductive biases. Useful biases often explo…

quant-ph20211 cited

Revisiting dequantization and quantum advantage in learning tasks

Jordan Cotler, Hsin-Yuan Huang, Jarrod R. McClean

It has been shown that the apparent advantage of some quantum machine learning algorithms may be efficiently replicated using classical algorithms with suitable data access -- a pr…