Zobrazeno 1 - 10
of 311
pro vyhledávání: '"Saberi, Amin"'
We study stationary online bipartite matching, where both types of nodes--offline and online--arrive according to Poisson processes. Offline nodes wait to be matched for some random time, determined by an exponential distribution, while online nodes
Externí odkaz:
http://arxiv.org/abs/2411.08218
Autor:
Pourreza, Mohammadreza, Li, Hailong, Sun, Ruoxi, Chung, Yeounoh, Talaei, Shayan, Kakkar, Gaurav Tarlok, Gan, Yu, Saberi, Amin, Ozcan, Fatma, Arik, Sercan O.
In tackling the challenges of large language model (LLM) performance for Text-to-SQL tasks, we introduce CHASE-SQL, a new framework that employs innovative strategies, using test-time compute in multi-agent modeling to improve candidate generation an
Externí odkaz:
http://arxiv.org/abs/2410.01943
Given a so called ''Sperner coloring'' of a triangulation of the $D$-dimensional simplex, Sperner's lemma guarantees the existence of a rainbow simplex, i.e. a simplex colored by all $D+1$ colors. However, finding a rainbow simplex was the first prob
Externí odkaz:
http://arxiv.org/abs/2409.15713
We study the polynomial-time approximability of the optimal online stochastic bipartite matching algorithm, initiated by Papadimitriou et al. (EC'21). Here, nodes on one side of the graph are given upfront, while at each time $t$, an online node and
Externí odkaz:
http://arxiv.org/abs/2407.15285
We study the stochastic online metric matching problem. In this problem, $m$ servers and $n$ requests are located in a metric space, where all servers are available upfront and requests arrive one at a time. In particular, servers are adversarially c
Externí odkaz:
http://arxiv.org/abs/2407.14785
We study online capacitated resource allocation, a natural generalization of online stochastic max-weight bipartite matching. This problem is motivated by ride-sharing and Internet advertising applications, where online arrivals may have the capacity
Externí odkaz:
http://arxiv.org/abs/2406.07757
Online Bayesian bipartite matching is a central problem in digital marketplaces and exchanges, including advertising, crowdsourcing, ridesharing, and kidney exchange. We introduce a graph neural network (GNN) approach that emulates the problem's comb
Externí odkaz:
http://arxiv.org/abs/2406.05959
Utilizing large language models (LLMs) for transforming natural language questions into SQL queries (text-to-SQL) is a promising yet challenging approach, particularly when applied to real-world databases with complex and extensive schemas. In partic
Externí odkaz:
http://arxiv.org/abs/2405.16755
This paper derives statistical guarantees for the performance of Graph Neural Networks (GNNs) in link prediction tasks on graphs generated by a graphon. We propose a linear GNN architecture (LG-GNN) that produces consistent estimators for the underly
Externí odkaz:
http://arxiv.org/abs/2402.02692
We propose a theoretical framework for training Graph Neural Networks (GNNs) on large input graphs via training on small, fixed-size sampled subgraphs. This framework is applicable to a wide range of models, including popular sampling-based GNNs, suc
Externí odkaz:
http://arxiv.org/abs/2310.10953