Search Results for author:
Found 7 papers, 4 papers with code
Evaluating AI systems under uncertain ground truth: a case study in dermatology
In contrast, we propose a framework where aggregation is done using a statistical model.
Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD
Neural network compression has been an increasingly important subject, not only due to its practical relevance, but also due to its theoretical implications, as there is an explicit connection between compressibility and generalization error.
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares
Recent studies have shown that heavy tails can emerge in stochastic optimization and that the heaviness of the tails have links to the generalization error.
DebiasedDTA: A Framework for Improving the Generalizability of Drug-Target Affinity Prediction Models
Here, we present DebiasedDTA, a novel drug-target affinity (DTA) prediction model training framework that addresses dataset biases to improve the generalizability of affinity prediction models.
Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks
Neural network compression techniques have become increasingly popular as they can drastically reduce the storage and computation requirements for very large networks.
Bayesian Model Selection for Identifying Markov Equivalent Causal Graphs
We believe that the Bayesian approach to causal discovery both allows the rich methodology of Bayesian inference to be used in various difficult aspects of this problem and provides a unifying framework to causal discovery research.
Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns
We introduce a dynamic generative model, Bayesian allocation model (BAM), which establishes explicit connections between nonnegative tensor factorization (NTF), graphical models of discrete probability distributions and their Bayesian extensions, and the topic models such as the latent Dirichlet allocation.
