Asia
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models
We propose a versatile framework that combines DEQ with off-the-shelf machine learning models for predicting Hamiltonians.
Streaming PCA for Markovian Data
Since its inception in 1982, Oja's algorithm has become an established method for streaming principle component analysis (PCA).
Simple, Scalable and Effective Clustering via One-Dimensional Projections
In large-scale applications, datasets often contain billions of high-dimensional points. Grouping similar data points into clusters is crucial for understanding and organizing datasets.
Reward Imputation with Sketching for Contextual Batched Bandits
Contextual batched bandit (CBB) is a setting where a batch of rewards is observed from the environment at the end of each episode, but the rewards of the non-executed actions are unobserved, resulting in partial-information feedback.
DiffHammer: Rethinking the Robustness of Diffusion-Based Adversarial Purification Kaibo Wang
Diffusion-based purification has demonstrated impressive robustness as an adversarial defense.
Class-Conditional Conformal Prediction with Many Classes
We propose a method called clustered conformal prediction that clusters together classes having "similar" conformal
Lo-Hi: Practical ML Drug Discovery Benchmark
Finding new drugs is getting harder and harder. One of the hopes of drug discovery is to use machine learning models to predict molecular properties.