4 papers
Scaling Point-in-Time Language Models
Bryan Kelly, Semyon Malamud, Johannes Schwab +1
Large language models trained on unrestricted internet corpora inevitably embed information from the future, introducing lookahead bias that compromises the validity of backtests a…
Training NTK to Generalize with KARE
Johannes Schwab, Bryan Kelly, Semyon Malamud +1
The performance of the data-dependent neural tangent kernel (NTK; Jacot et al. (2018)) associated with a trained deep neural network (DNN) often matches or exceeds that of the full…
Benign Autoencoders
Semyon Malamud, Teng Andrea Xu, Antoine Didisheim
Recent progress in Generative Artificial Intelligence (AI) relies on efficient data representations, often featuring encoder-decoder architectures. We formalize the mathematical pr…
Personalization for Web-based Services using Offline Reinforcement Learning
Pavlos Athanasios Apostolopoulos, Zehui Wang, Hanson Wang +4
Large-scale Web-based services present opportunities for improving UI policies based on observed user interactions. We address challenges of learning such policies through model-fr…