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20182021
most citedCombinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning

140 citations · 228 across the 18 of their papers we have counts for

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11 papers · 1 filter

cs.LG202121 cited

AlphaD3M: Machine Learning Pipeline Synthesis

Iddo Drori, Yamuna Krishnamurthy, Remi Rampin +5

We introduce AlphaD3M, an automatic machine learning (AutoML) system based on meta reinforcement learning using sequence models with self play. AlphaD3M is based on edit operations…

cs.LG2021

Predicting Critical Biogeochemistry of the Southern Ocean for Climate Monitoring

Ellen Park, Jae Deok Kim, Nadege Aoki +5

The Biogeochemical-Argo (BGC-Argo) program is building a network of globally distributed, sensor-equipped robotic profiling floats, improving our understanding of the climate syste…

cs.LG2021

Predicting Atlantic Multidecadal Variability

Glenn Liu, Peidong Wang, Matthew Beveridge +2

Atlantic Multidecadal Variability (AMV) describes variations of North Atlantic sea surface temperature with a typical cycle of between 60 and 70 years. AMV strongly impacts local c…

cs.LG20217 cited

Pedestrian Wind Factor Estimation in Complex Urban Environments

Sarah Mokhtar, Matthew Beveridge, Yumeng Cao +1

Urban planners and policy makers face the challenge of creating livable and enjoyable cities for larger populations in much denser urban conditions. While the urban microclimate ho…

cs.LG20215 cited

Solving Machine Learning Problems

Sunny Tran, Pranav Krishna, Ishan Pakuwal +4

Can a machine learn Machine Learning? This work trains a machine learning model to solve machine learning problems from a University undergraduate level course. We generate a new t…

cs.LG20211 cited

Privileged Zero-Shot AutoML

Nikhil Singh, Brandon Kates, Jeff Mentch +3

This work improves the quality of automated machine learning (AutoML) systems by using dataset and function descriptions while significantly decreasing computation time from minute…