activity
20162022
most citedError Metrics for Learning Reliable Manifolds from Streaming Data

15 citations · 17 across the 4 of their papers we have counts for

collaborators

5 papers

cs.MA2022

ACHORD: Communication-Aware Multi-Robot Coordination with Intermittent Connectivity

Maira Saboia, Lillian Clark, Vivek Thangavelu +16

Communication is an important capability for multi-robot exploration because (1) inter-robot communication (comms) improves coverage efficiency and (2) robot-to-base comms improves…

cs.CV2021★ 1 cited

Active Face Frontalization using Commodity Unmanned Aerial Vehicles

Nagashri Lakshminarayana, Yifang Liu, Karthik Dantu +2

This paper describes a system by which Unmanned Aerial Vehicles (UAVs) can gather high-quality face images that can be used in biometric identification tasks. Success in face-based…

stat.ML2018

Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes

Frank Schoeneman, Varun Chandola, Nils Napp +2

Scientific and engineering processes deliver massive high-dimensional data sets that are generated as non-linear transformations of an initial state and few process parameters. Map…

stat.ML2016★ 15 cited

Error Metrics for Learning Reliable Manifolds from Streaming Data

Frank Schoeneman, Suchismit Mahapatra, Varun Chandola +2

Spectral dimensionality reduction is frequently used to identify low-dimensional structure in high-dimensional data. However, learning manifolds, especially from the streaming data…

stat.ML2016★ 1 cited

On Optimality Conditions for Auto-Encoder Signal Recovery

Devansh Arpit, Yingbo Zhou, Hung Q. Ngo +2

Auto-Encoders are unsupervised models that aim to learn patterns from observed data by minimizing a reconstruction cost. The useful representations learned are often found to be sp…