504 citations · 2k across the 109 of their papers we have counts for
8 papers · 1 filter
Graph Matching via Optimal Transport
Ali Saad-Eldin, Benjamin D. Pedigo, Carey E. Priebe +1
The graph matching problem seeks to find an alignment between the nodes of two graphs that minimizes the number of adjacency disagreements. Solving the graph matching is increasing…
Extremely Simple Streaming Forest
Haoyin Xu, Jayanta Dey, Sambit Panda +1
Decision forests, including random forests and gradient boosting trees, remain the leading machine learning methods for many real-world data problems, especially on tabular data. H…
Towards a theory of out-of-distribution learning
Jayanta Dey, Ali Geisa, Ronak Mehta +7
Learning is a process wherein a learning agent enhances its performance through exposure of experience or data. Throughout this journey, the agent may encounter diverse learning en…
When are Deep Networks really better than Decision Forests at small sample sizes, and how?
Haoyin Xu, Kaleab A. Kinfu, Will LeVine +9
Deep networks and decision forests (such as random forests and gradient boosted trees) are the leading machine learning methods for structured and tabular data, respectively. Many…
Federated Causal Inference in Heterogeneous Observational Data
Ruoxuan Xiong, Allison Koenecke, Michael Powell +3
We are interested in estimating the effect of a treatment applied to individuals at multiple sites, where data is stored locally for each site. Due to privacy constraints, individu…
Hidden Markov Modeling for Maximum Likelihood Neuron Reconstruction
Thomas L. Athey, Daniel J. Tward, Ulrich Mueller +2
Recent advances in brain clearing and imaging have made it possible to image entire mammalian brains at sub-micron resolution. These images offer the potential to assemble brain-wi…