output
20192024
most citedMulti-Modal Federated Learning for Cancer Staging over Non-IID Datasets with Unbalanced Modalities

22 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

6 papers

cs.LG2024

FairHome: A Fair Housing and Fair Lending Dataset

Anusha Bagalkotkar, Aveek Karmakar, Gabriel Arnson +1

We present a Fair Housing and Fair Lending dataset (FairHome): A dataset with around 75,000 examples across 9 protected categories. To the best of our knowledge, FairHome is the fi…

cs.LG2024★ 22 cited

Multi-Modal Federated Learning for Cancer Staging over Non-IID Datasets with Unbalanced Modalities

Kasra Borazjani, Naji Khosravan, Leslie Ying +1

The use of machine learning (ML) for cancer staging through medical image analysis has gained substantial interest across medical disciplines. When accompanied by the innovative fe…

cs.CV2022★ 6 cited

Generating Topological Structure of Floorplans from Room Attributes

Yin Yu, Hutchcroft Will, Khosravan Naji +3

Analysis of indoor spaces requires topological information. In this paper, we propose to extract topological information from room attributes using what we call Iterative and adapt…

cs.SD2020★ 3 cited

Modeling Baroque Two-Part Counterpoint with Neural Machine Translation

Eric P. Nichols, Stefano Kalonaris, Gianluca Micchi +1

We propose a system for contrapuntal music generation based on a Neural Machine Translation (NMT) paradigm. We consider Baroque counterpoint and are interested in modeling the inte…

cs.LG2020

Root Cause Detection Among Anomalous Time Series Using Temporal State Alignment

Sayan Chakraborty, Smit Shah, Kiumars Soltani +1

The recent increase in the scale and complexity of software systems has introduced new challenges to the time series monitoring and anomaly detection process. A major drawback of e…

cs.CV2019★ 4 cited

Pano Popups: Indoor 3D Reconstruction with a Plane-Aware Network

Marc Eder, Pierre Moulon, Li Guan

In this work we present a method to train a plane-aware convolutional neural network for dense depth and surface normal estimation as well as plane boundaries from a single indoor…