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Found 7 papers, 1 papers with code
Partial differential equation-based inference of migration and proliferation mechanisms in cancer cell populations
Targeting signaling pathways that drive cancer cell migration or proliferation is a common therapeutic approach.
Predicting Out-of-Distribution Error with Confidence Optimal Transport
Out-of-distribution (OOD) data poses serious challenges in deployed machine learning models as even subtle changes could incur significant performance drops.
Best Arm Identification with Safety Constraints
The best arm identification problem in the multi-armed bandit setting is an excellent model of many real-world decision-making problems, yet it fails to capture the fact that in the real-world, safety constraints often must be met while learning.
Max-Min Grouped Bandits
In this paper, we introduce a multi-armed bandit problem termed max-min grouped bandits, in which the arms are arranged in possibly-overlapping groups, and the goal is to find the group whose worst arm has the highest mean reward.
Exploring General Intelligence of Program Analysis for Multiple Tasks
To this end, we explore a generic program embedding approach that aim at solving multiple program analysis tasks.
GRAPHSPY: Fused Program Semantic-Level Embedding via Graph Neural Networks for Dead Store Detection
To this end, we propose a learning-aided approach to identify unnecessary memory operations intelligently with low overhead.
System inference for the spatio-temporal evolution of infectious diseases: Michigan in the time of COVID-19
We extend the classical SIR model of infectious disease spread to account for time dependence in the parameters, which also include diffusivities.
