Summary of Clipping Improves Adam-norm and Adagrad-norm When the Noise Is Heavy-tailed, by Savelii Chezhegov et al.
Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailedby Savelii Chezhegov, Yaroslav Klyukin, Andrei…
Summary of Generative Assignment Flows For Representing and Learning Joint Distributions Of Discrete Data, by Bastian Boll et al.
Generative Assignment Flows for Representing and Learning Joint Distributions of Discrete Databy Bastian Boll, Daniel…
Summary of Why Has Predicting Downstream Capabilities Of Frontier Ai Models with Scale Remained Elusive?, by Rylan Schaeffer et al.
Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?by Rylan Schaeffer,…
Summary of A Probabilistic Approach to Learning the Degree Of Equivariance in Steerable Cnns, by Lars Veefkind et al.
A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNsby Lars Veefkind, Gabriele…
Summary of Reassessing How to Compare and Improve the Calibration Of Machine Learning Models, by Muthu Chidambaram and Rong Ge
Reassessing How to Compare and Improve the Calibration of Machine Learning Modelsby Muthu Chidambaram, Rong…
Summary of Reconciling Heterogeneous Effects in Causal Inference, by Audrey Chang et al.
Reconciling Heterogeneous Effects in Causal Inferenceby Audrey Chang, Emily Diana, Alexander Williams TolbertFirst submitted to…
Summary of Transfer Learning For Latent Variable Network Models, by Akhil Jalan et al.
Transfer Learning for Latent Variable Network Modelsby Akhil Jalan, Arya Mazumdar, Soumendu Sundar Mukherjee, Purnamrita…
Summary of Adversarial Moment-matching Distillation Of Large Language Models, by Chen Jia
Adversarial Moment-Matching Distillation of Large Language Modelsby Chen JiaFirst submitted to arxiv on: 5 Jun…
Summary of Ai-sampler: Adversarial Learning Of Markov Kernels with Involutive Maps, by Evgenii Egorov and Ricardo Valperga et al.
Ai-Sampler: Adversarial Learning of Markov kernels with involutive mapsby Evgenii Egorov, Ricardo Valperga, Efstratios GavvesFirst…
Summary of Learning-rate-free Stochastic Optimization Over Riemannian Manifolds, by Daniel Dodd et al.
Learning-Rate-Free Stochastic Optimization over Riemannian Manifoldsby Daniel Dodd, Louis Sharrock, Christopher NemethFirst submitted to arxiv…