Summary of Survey Of Computerized Adaptive Testing: a Machine Learning Perspective, by Qi Liu et al.
Survey of Computerized Adaptive Testing: A Machine Learning Perspectiveby Qi Liu, Yan Zhuang, Haoyang Bi,…
Summary of Comparing Hyper-optimized Machine Learning Models For Predicting Efficiency Degradation in Organic Solar Cells, by David Valiente et al.
Comparing Hyper-optimized Machine Learning Models for Predicting Efficiency Degradation in Organic Solar Cellsby David Valiente,…
Summary of Functional Bilevel Optimization For Machine Learning, by Ieva Petrulionyte et al.
Functional Bilevel Optimization for Machine Learningby Ieva Petrulionyte, Julien Mairal, Michael ArbelFirst submitted to arxiv…
Summary of Towards Stable Machine Learning Model Retraining Via Slowly Varying Sequences, by Dimitris Bertsimas et al.
Towards Stable Machine Learning Model Retraining via Slowly Varying Sequencesby Dimitris Bertsimas, Vassilis Digalakis Jr,…
Summary of Maximum Likelihood Estimation on Stochastic Blockmodels For Directed Graph Clustering, by Mihai Cucuringu et al.
Maximum Likelihood Estimation on Stochastic Blockmodels for Directed Graph Clusteringby Mihai Cucuringu, Xiaowen Dong, Ning…
Summary of Self-improved Learning For Scalable Neural Combinatorial Optimization, by Fu Luo et al.
Self-Improved Learning for Scalable Neural Combinatorial Optimizationby Fu Luo, Xi Lin, Zhenkun Wang, Xialiang Tong,…
Summary of Fine-tuning Language Models with Reward Learning on Policy, by Hao Lang et al.
Fine-Tuning Language Models with Reward Learning on Policyby Hao Lang, Fei Huang, Yongbin LiFirst submitted…
Summary of Offline Imitation Learning From Multiple Baselines with Applications to Compiler Optimization, by Teodor V. Marinov et al.
Offline Imitation Learning from Multiple Baselines with Applications to Compiler Optimizationby Teodor V. Marinov, Alekh…
Summary of Disentangling Length From Quality in Direct Preference Optimization, by Ryan Park and Rafael Rafailov and Stefano Ermon and Chelsea Finn
Disentangling Length from Quality in Direct Preference Optimizationby Ryan Park, Rafael Rafailov, Stefano Ermon, Chelsea…
Summary of From Activation to Initialization: Scaling Insights For Optimizing Neural Fields, by Hemanth Saratchandran et al.
From Activation to Initialization: Scaling Insights for Optimizing Neural Fieldsby Hemanth Saratchandran, Sameera Ramasinghe, Simon…