21 citations · 44 across the 22 of their papers we have counts for
24 papers
DLB: Distributed Load Balancing at Scale for Generative AI Inference
Santiago R. Balseiro, Bartek Wydrowski, Sameer Agarwal +11
The reliance on scarce and expensive accelerators such as GPUs and TPUs in modern datacenters places unprecedented demands on backend infrastructure. For workloads characterized by…
Position Auctions in AI-Generated Content
Santiago Balseiro, Kshipra Bhawalkar, Yuan Deng +7
We consider an extension to the classic position auctions in which sponsored creatives can be added within AI generated content rather than shown in predefined slots. New challenge…
Load Balancing with Network Latencies via Distributed Gradient Descent
Santiago R. Balseiro, Vahab S. Mirrokni, Bartek Wydrowski
Motivated by the growing demand for serving large language model inference requests, we study distributed load balancing for global serving systems with network latencies. We consi…
Distributed Load Balancing with Workload-Dependent Service Rates
Wenxin Zhang, Santiago R. Balseiro, Robert Kleinberg +3
Modern service systems, including cloud platforms and large language model inference endpoints, must distribute jobs across servers whose processing speeds depend on current worklo…
Auto-bidding and Auctions in Online Advertising: A Survey
Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro +23
In this survey, we summarize recent developments in research fueled by the growing adoption of automated bidding strategies in online advertising. We explore the challenges and opp…
Battery Operations in Electricity Markets: Strategic Behavior and Distortions
Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes +1
Battery storage can reduce electricity generation costs by shifting energy across time, but as privately owned batteries become large, they may also be able to exert market power.…
The Best of Many Robustness Criteria in Decision Making: Formulation and Application to Robust Pricing
Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes
In robust decision-making under non-Bayesian uncertainty, different robust optimization criteria, such as maximin performance, minimax regret, and maximin ratio, have been proposed…
Dynamic Pricing for Reusable Resources: The Power of Two Prices
Santiago R. Balseiro, Will Ma, Wenxin Zhang
Motivated by real-world applications such as rental and cloud computing services, we investigate pricing for reusable resources. We consider a system where a single resource with a…
Robust Auction Design with Support Information
Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes
A seller wants to sell an item to buyers. Buyer valuations are drawn i.i.d. from a distribution unknown to the seller; the seller only knows that the support is included in $[a…
Robust Budget Pacing with a Single Sample
Santiago Balseiro, Rachitesh Kumar, Vahab Mirrokni +2
Major Internet advertising platforms offer budget pacing tools as a standard service for advertisers to manage their ad campaigns. Given the inherent non-stationarity in an adverti…
A Field Guide for Pacing Budget and ROS Constraints
Santiago R. Balseiro, Kshipra Bhawalkar, Zhe Feng +4
Budget pacing is a popular service that has been offered by major internet advertising platforms since their inception. Budget pacing systems seek to optimize advertiser returns su…
Online Resource Allocation under Horizon Uncertainty
Santiago Balseiro, Christian Kroer, Rachitesh Kumar
We study stochastic online resource allocation: a decision maker needs to allocate limited resources to stochastically-generated sequentially-arriving requests in order to maximize…
Uniformly Bounded Regret in Dynamic Fair Allocation
Santiago R. Balseiro, Shangzhou Xia
We study a dynamic allocation problem in which sequentially arriving divisible resources are to be allocated to a number of agents with linear utilities. The marginal utilities…
On the Robustness of Second-Price Auctions in Prior-Independent Mechanism Design
Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes
Classical Bayesian mechanism design relies on the common prior assumption, but such prior is often not available in practice. We study the design of prior-independent mechanisms th…
Single-Leg Revenue Management with Advice
Santiago Balseiro, Christian Kroer, Rachitesh Kumar
Single-leg revenue management is a foundational problem of revenue management that has been particularly impactful in the airline and hotel industry: Given units of a resource,…
Analysis of Dual-Based PID Controllers through Convolutional Mirror Descent
Santiago R. Balseiro, Haihao Lu, Vahab Mirrokni +1
Dual-based proportional-integral-derivative (PID) controllers are often employed in practice to solve online allocation problems with global constraints, such as budget pacing in o…
Robust Auction Design in the Auto-bidding World
Santiago Balseiro, Yuan Deng, Jieming Mao +2
In classic auction theory, reserve prices are known to be effective for improving revenue for the auctioneer against quasi-linear utility maximizing bidders. The introduction of re…
Mechanism Design under Approximate Incentive Compatibility
Santiago Balseiro, Omar Besbes, Francisco Castro
A fundamental assumption in classical mechanism design is that buyers are perfect optimizers. However, in practice, buyers may be limited by their computational capabilities or a l…
Contextual Standard Auctions with Budgets: Revenue Equivalence and Efficiency Guarantees
Santiago Balseiro, Christian Kroer, Rachitesh Kumar
The internet advertising market is a multi-billion dollar industry, in which advertisers buy thousands of ad placements every day by repeatedly participating in auctions. An import…
The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems
Santiago Balseiro, Haihao Lu, Vahab Mirrokni
Online allocation problems with resource constraints are central problems in revenue management and online advertising. In these problems, requests arrive sequentially during a fin…
Regularized Online Allocation Problems: Fairness and Beyond
Santiago Balseiro, Haihao Lu, Vahab Mirrokni
Online allocation problems with resource constraints have a rich history in operations research. In this paper, we introduce the \emph{regularized online allocation problem}, a var…
Dual Mirror Descent for Online Allocation Problems
Haihao Lu, Santiago Balseiro, Vahab Mirrokni
We consider online allocation problems with concave revenue functions and resource constraints, which are central problems in revenue management and online advertising. In these se…
Contextual Bandits with Cross-learning
Santiago Balseiro, Negin Golrezaei, Mohammad Mahdian +2
In the classical contextual bandits problem, in each round , a learner observes some context , chooses some action to perform, and receives some reward . We c…
Yield Optimization of Display Advertising with Ad Exchange
Santiago Balseiro, Jon Feldman, Vahab Mirrokni +1
In light of the growing market of Ad Exchanges for the real-time sale of advertising slots, publishers face new challenges in choosing between the allocation of contract-based rese…