most citedConvergence rate of stochastic k-means

8 citations · 16 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2023

Multi-decadal Sea Level Prediction using Neural Networks and Spectral Clustering on Climate Model Large Ensembles and Satellite Altimeter Data

Saumya Sinha, John Fasullo, R. Steven Nerem +1

Sea surface height observations provided by satellite altimetry since 1993 show a rising rate (3.4 mm/year) for global mean sea level. While on average, sea level has risen 10 cm o…

cs.CV2023

STint: Self-supervised Temporal Interpolation for Geospatial Data

Nidhin Harilal, Bri-Mathias Hodge, Aneesh Subramanian +1

Supervised and unsupervised techniques have demonstrated the potential for temporal interpolation of video data. Nevertheless, most prevailing temporal interpolation techniques hin…

physics.ao-ph2023

Sea level Projections with Machine Learning using Altimetry and Climate Model ensembles

Saumya Sinha, John Fasullo, R. Steven Nerem +1

Satellite altimeter observations retrieved since 1993 show that the global mean sea level is rising at an unprecedented rate (3.4mm/year). With almost three decades of observations…

cs.AI20236 cited

Reflections from the Workshop on AI-Assisted Decision Making for Conservation

Lily Xu, Esther Rolf, Sara Beery +21

In this white paper, we synthesize key points made during presentations and discussions from the AI-Assisted Decision Making for Conservation workshop, hosted by the Center for Res…

cs.LG20168 cited

Convergence rate of stochastic k-means

Cheng Tang, Claire Monteleoni

We analyze online \cite{BottouBengio} and mini-batch \cite{Sculley} -means variants. Both scale up the widely used -means algorithm via stochastic approximation, and have bec…

cs.LG20162 cited

Convergence rate of stochastic k-means

Cheng Tang, Claire Monteleoni

We analyze online and mini-batch k-means variants. Both scale up the widely used Lloyd 's algorithm via stochastic approximation, and have become popular for large-scale clustering…