Summary of Age-of-gradient Updates For Federated Learning Over Random Access Channels, by Yu Heng Wu et al.
Age-of-Gradient Updates for Federated Learning over Random Access Channelsby Yu Heng Wu, Houman Asgari, Stefano…
Summary of Understanding Likelihood Over-optimisation in Direct Alignment Algorithms, by Zhengyan Shi et al.
Understanding Likelihood Over-optimisation in Direct Alignment Algorithmsby Zhengyan Shi, Sander Land, Acyr Locatelli, Matthieu Geist,…
Summary of Selection-p: Self-supervised Task-agnostic Prompt Compression For Faithfulness and Transferability, by Tsz Ting Chung et al.
Selection-p: Self-Supervised Task-Agnostic Prompt Compression for Faithfulness and Transferabilityby Tsz Ting Chung, Leyang Cui, Lemao…
Summary of Foogd: Federated Collaboration For Both Out-of-distribution Generalization and Detection, by Xinting Liao et al.
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detectionby Xinting Liao, Weiming Liu, Pengyang Zhou,…
Summary of Neural Symbolic Regression Of Complex Network Dynamics, by Haiquan Qiu et al.
Neural Symbolic Regression of Complex Network Dynamicsby Haiquan Qiu, Shuzhi Liu, Quanming YaoFirst submitted to…
Summary of Statistical Properties Of Deep Neural Networks with Dependent Data, by Chad Brown
Statistical Properties of Deep Neural Networks with Dependent Databy Chad BrownFirst submitted to arxiv on:…
Summary of Non-convergence to Global Minimizers in Data Driven Supervised Deep Learning: Adam and Stochastic Gradient Descent Optimization Provably Fail to Converge to Global Minimizers in the Training Of Deep Neural Networks with Relu Activation, by Thang Do and Sonja Hannibal and Arnulf Jentzen
Non-convergence to global minimizers in data driven supervised deep learning: Adam and stochastic gradient descent…
Summary of Stein Variational Evolution Strategies, by Cornelius V. Braun et al.
Stein Variational Evolution Strategiesby Cornelius V. Braun, Robert T. Lange, Marc ToussaintFirst submitted to arxiv…
Summary of A Stochastic Approach to Bi-level Optimization For Hyperparameter Optimization and Meta Learning, by Minyoung Kim et al.
A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learningby Minyoung Kim, Timothy…
Summary of Neural Quasiprobabilistic Likelihood Ratio Estimation with Negatively Weighted Data, by Matthew Drnevich et al.
Neural Quasiprobabilistic Likelihood Ratio Estimation with Negatively Weighted Databy Matthew Drnevich, Stephen Jiggins, Judith Katzy,…