Improving the Capabilities of Large Language Model Based Marketing Analytics Copilots With Semantic Search And…
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modellingby Grigory Bartosh, Dmitry Vetrov,…
SOPHON: Non-Fine-Tunable Learning to Restrain Task Transferability For Pre-trained Modelsby Jiangyi Deng, Shengyuan Pang, Yanjiao…
decoupleQ: Towards 2-bit Post-Training Uniform Quantization via decoupling Parameters into Integer and Floating Pointsby Yi…
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximationby Jianliang He, Han Zhong, Zhuoran…
Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization with Representation Learningby Jie Chen, Pengfei Ou, Yuxin…
Neural Methods for Amortized Inferenceby Andrew Zammit-Mangion, Matthew Sainsbury-Dale, Raphaël HuserFirst submitted to arxiv on:…
A Mean-Field Analysis of Neural Stochastic Gradient Descent-Ascent for Functional Minimax Optimizationby Yuchen Zhu, Yufeng…
Expected Coordinate Improvement for High-Dimensional Bayesian Optimizationby Dawei ZhanFirst submitted to arxiv on: 18 Apr…
Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Modelsby Shivvrat Arya,…