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Found 5 papers, 2 papers with code
GPT4 is Slightly Helpful for Peer-Review Assistance: A Pilot Study
In this pilot study, we investigate the use of GPT4 to assist in the peer-review process.
Layer-Wise Feedback Alignment is Conserved in Deep Neural Networks
In the quest to enhance the efficiency and bio-plausibility of training deep neural networks, Feedback Alignment (FA), which replaces the backward pass weights with random matrices in the training process, has emerged as an alternative to traditional backpropagation.
No Bidding, No Regret: Pairwise-Feedback Mechanisms for Digital Goods and Data Auctions
The mechanism's novelty lies in using pairwise comparisons for eliciting information from the bidder, arguably easier for humans than assigning a numerical value.
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions
We study the design of loss functions for click-through rates (CTR) to optimize (social) welfare in advertising auctions.
Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle
Double descent is a surprising phenomenon in machine learning, in which as the number of model parameters grows relative to the number of data, test error drops as models grow ever larger into the highly overparameterized (data undersampled) regime.
