Search Results for author:
Found 8 papers, 2 papers with code
Temporal Network Creation Games
However, many real-world networks are not shaped by a central designer but instead they emerge and evolve by the interaction of many strategic agents.
Deep Distance Sensitivity Oracles
More specifically, we utilize the combinatorial structure of replacement paths as a concatenation of shortest paths and use deep learning to find the pivot nodes for stitching shortest paths into replacement paths.
Fast Feature Selection with Fairness Constraints
We study the fundamental problem of selecting optimal features for model construction.
Non-Volatile Memory Accelerated Geometric Multi-Scale Resolution Analysis
Dimensionality reduction algorithms are frequently used to augment downstream tasks such as machine learning, data science, and also are exploratory methods for understanding complex phenomena.
Non-Volatile Memory Accelerated Posterior Estimation
Bayesian inference allows machine learning models to express uncertainty.
What's Wrong with Deep Learning in Tree Search for Combinatorial Optimization
Second, using our benchmark suite, we conduct an in-depth analysis of the popular guided tree search algorithm by Li et al. [NeurIPS 2018], testing various configurations on small and large synthetic and real-world graphs.
What’s Wrong with Deep Learning in Tree Search for Combinatorial Optimization
Second, using our benchmark suite, we conduct an in-depth analysis of the popular guided tree search algorithm by Li et al. [NeurIPS 2018], testing various configurations on small and large synthetic and real-world graphs.
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
This is especially true for handwritten text recognition (HTR), where each author has a unique style, unlike printed text, where the variation is smaller by design.
