Africa
Optimal Algorithms for Learning Partitions with Faulty Oracles
This models applications where learners crowdsource information from non-expert human workers or conduct noisy experiments to determine group structure. The learner aims to exactly recover a partition by submitting queries of the form "are
On Reinforcement Learningand Distribution Matchingfor Fine-Tuning Language Models withno Catastrophic Forgetting
Twoofthemcanbecharacterizedas "Reward Maximization" (RM): Standard Policy Gradients (PG) and KL-control.
Not All Out-of-Distribution Data Are Harmful to Open-Set Active Learning Y ang
Recall (higher is better): the ratio of selected ID instances to the total number of ID instances.
Not All Out-of-Distribution Data Are Harmful to Open-Set Active Learning Y ang
Recall (higher is better): the ratio of selected ID instances to the total number of ID instances.
OnlineMeta-LearningviaLearningwith Layer-DistributedMemory
Methods differ in the underlying architecture and mechanisms they use to support adaptation.
EcoLight
Effective intersection control can play an important role in reducing traffic congestion and associated vehicular emissions.
How to Select Which Active Learning Strategy is Best Suited for Y our Specific Problem and Budget Guy Hacohen, Daphna Weinshall School of Computer Science & Engineering
In the traditional supervised learning framework, active learning enables the learner to actively engage in the construction of the labeled training set by selecting a fixed-sized subset of unlabeled examples for labeling by an oracle, where the number of labels requested is referred to as the budget .