895 citations · 1.4k across the 15 of their papers we have counts for
15 papers
Coordinated Dynamic Bidding in Repeated Second-Price Auctions with Budgets
Yurong Chen, Qian Wang, Zhijian Duan +4
In online ad markets, a rising number of advertisers are employing bidding agencies to participate in ad auctions. These agencies are specialized in designing online algorithms and…
A Scalable Neural Network for DSIC Affine Maximizer Auction Design
Zhijian Duan, Haoran Sun, Yurong Chen +1
Automated auction design aims to find empirically high-revenue mechanisms through machine learning. Existing works on multi item auction scenarios can be roughly divided into Regre…
Score-based Continuous-time Discrete Diffusion Models
Haoran Sun, Lijun Yu, Bo Dai +2
Score-based modeling through stochastic differential equations (SDEs) has provided a new perspective on diffusion models, and demonstrated superior performance on continuous data.…
Optimal Scaling for Locally Balanced Proposals in Discrete Spaces
Haoran Sun, Hanjun Dai, Dale Schuurmans
Optimal scaling has been well studied for Metropolis-Hastings (M-H) algorithms in continuous spaces, but a similar understanding has been lacking in discrete spaces. Recently, a fa…
A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language
Bing Su, Dazhao Du, Zhao Yang +6
Although artificial intelligence (AI) has made significant progress in understanding molecules in a wide range of fields, existing models generally acquire the single cognitive abi…
Multimodal foundation models are better simulators of the human brain
Haoyu Lu, Qiongyi Zhou, Nanyi Fei +8
Multimodal learning, especially large-scale multimodal pre-training, has developed rapidly over the past few years and led to the greatest advances in artificial intelligence (AI).…
Annealed Training for Combinatorial Optimization on Graphs
Haoran Sun, Etash K. Guha, Hanjun Dai
The hardness of combinatorial optimization (CO) problems hinders collecting solutions for supervised learning. However, learning neural networks for CO problems is notoriously diff…
Discrete Langevin Sampler via Wasserstein Gradient Flow
Haoran Sun, Hanjun Dai, Bo Dai +2
It is known that gradient-based MCMC samplers for continuous spaces, such as Langevin Monte Carlo (LMC), can be derived as particle versions of a gradient flow that minimizes KL di…
To Supervise or Not: How to Effectively Learn Wireless Interference Management Models?
Bingqing Song, Haoran Sun, Wenqiang Pu +2
Machine learning has become successful in solving wireless interference management problems. Different kinds of deep neural networks (DNNs) have been trained to accomplish key task…
Towards artificial general intelligence via a multimodal foundation model
Nanyi Fei, Zhiwu Lu, Yizhao Gao +9
The fundamental goal of artificial intelligence (AI) is to mimic the core cognitive activities of human. Despite tremendous success in the AI research, most of existing methods hav…
Human-verifiable proofs in the theory of word-representable graphs
Sergey Kitaev, Haoran Sun
A graph is word-representable if it can be represented in a certain way using alternation of letters in words. Word-representable graphs generalise several important and well-studi…
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms
Xiangyi Chen, Tiancong Chen, Haoran Sun +2
Recently, there is a growing interest in the study of median-based algorithms for distributed non-convex optimization. Two prominent such algorithms include signSGD with majority v…
Distributed Non-Convex First-Order Optimization and Information Processing: Lower Complexity Bounds and Rate Optimal Algorithms
Haoran Sun, Mingyi Hong
We consider a class of popular distributed non-convex optimization problems, in which agents connected by a network collectively optimize a sum of smooth (possibly no…
Learning to Optimize: Training Deep Neural Networks for Wireless Resource Management
Haoran Sun, Xiangyi Chen, Qingjiang Shi +3
For the past couple of decades, numerical optimization has played a central role in addressing wireless resource management problems such as power control and beamformer design. Ho…
Inexact Block Coordinate Descent Methods For Symmetric Nonnegative Matrix Factorization
Qingjiang Shi, Haoran Sun, Songtao Lu +2
Symmetric nonnegative matrix factorization (SNMF) is equivalent to computing a symmetric nonnegative low rank approximation of a data similarity matrix. It inherits the good data i…