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We introduce algorithms for online, full-information prediction that are competitive with contextual tree experts of unknown complexity, in both probabilistic and adversarial settings. We show that by incorporating a probabilistic framework…

Machine Learning · Computer Science 2018-05-23 Vidya Muthukumar , Mitas Ray , Anant Sahai , Peter L. Bartlett

We consider a scheduling problem where a cloud service provider has multiple units of a resource available over time. Selfish clients submit jobs, each with an arrival time, deadline, length, and value. The service provider's goal is to…

Computer Science and Game Theory · Computer Science 2017-03-03 Shuchi Chawla , Nikhil Devanur , Janardhan Kulkarni , Rad Niazadeh

We present a new variant of the secretary problem. Let $A$ be a totally ordered set of $n$ \emph{applicants}. Given $P\subseteq A$ and $x\in A$, let $rr(P,x)=\vert\{z\in P \mid z\leq x\}\vert\mbox{ }$ be the \emph{relative rank of} $x$…

Probability · Mathematics 2023-07-10 Josef Rukavicka

In learning-augmented online algorithms, predictions are usually valued for what they say: a value estimate, a solution, or an algorithmic recommendation. This paper shows that predictions can also be valuable solely due to their arrival…

Data Structures and Algorithms · Computer Science 2026-05-22 Franziska Eberle , Alexander Lindermayr

One of the classic problems in online decision-making is the *secretary problem* where to goal is to maximize the probability of choosing the largest number from a randomly ordered sequence. A natural extension allows selecting multiple…

Data Structures and Algorithms · Computer Science 2025-01-16 Kiarash Banihashem , MohammadTaghi Hajiaghayi , Dariusz R. Kowalski , Piotr Krysta , Danny Mittal , Jan Olkowski

The theory of reinforcement learning has focused on two fundamental problems: achieving low regret, and identifying $\epsilon$-optimal policies. While a simple reduction allows one to apply a low-regret algorithm to obtain an…

Machine Learning · Computer Science 2022-06-23 Andrew Wagenmaker , Max Simchowitz , Kevin Jamieson

We initiate the study of a repeated principal-agent problem over a finite horizon $T$, where a principal sequentially interacts with $K\geq 2$ types of agents arriving in an adversarial order. At each round, the principal strategically…

Computer Science and Game Theory · Computer Science 2025-08-05 Junyan Liu , Arnab Maiti , Artin Tajdini , Kevin Jamieson , Lillian J. Ratliff

We consider the classical online bipartite matching problem in the probe-commit model. In this problem, when an online vertex arrives, its edges must be probed to determine if they exist, based on known edge probabilities. A probing…

Data Structures and Algorithms · Computer Science 2024-12-16 Allan Borodin , Calum MacRury

Given integers $1\leq k<n$, the Gusein-Zade version of a generalized secretary problem is to choose one of the $k$ best of $n$ candidates for a secretary, which are interviewing in random order. The stopping rule in the selection is based…

Combinatorics · Mathematics 2016-10-19 Adam Woryna

We consider a variation on the problem of prediction with expert advice, where new forecasters that were unknown until then may appear at each round. As often in prediction with expert advice, designing an algorithm that achieves…

Machine Learning · Statistics 2017-09-01 Jaouad Mourtada , Odalric-Ambrym Maillard

We consider the problem of repeatedly choosing policies to maximize social welfare. Welfare is a weighted sum of private utility and public revenue. Earlier outcomes inform later policies. Utility is not observed, but indirectly inferred.…

Econometrics · Economics 2024-07-30 Nicolo Cesa-Bianchi , Roberto Colomboni , Maximilian Kasy

We study the fundamental problem of designing contracts in principal-agent problems under uncertainty. Previous works mostly addressed Bayesian settings in which principal's uncertainty is modeled as a probability distribution over agent's…

Computer Science and Game Theory · Computer Science 2024-02-22 Martino Bernasconi , Matteo Castiglioni , Alberto Marchesi

Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized allocations were close to the best feasible choices in hindsight. We present a retrospective…

Econometrics · Economics 2026-05-01 Nilavra Pathak , Olivier Jeunen , Eric Lambert

We consider budget feasible mechanisms for procurement auctions with additive valuation functions. For the divisible case, where agents can be allocated fractionally, there exists an optimal mechanism with approximation guarantee $e/(e-1)$…

Computer Science and Game Theory · Computer Science 2022-09-02 Sophie Klumper , Guido Schäfer

In modern advertising platforms, learning algorithms are deployed by budget-constrained bidders to maximize their accumulated value. These algorithms often offer classical utility guarantees like no-regret, i.e., the agent's utility is at…

Computer Science and Game Theory · Computer Science 2026-02-23 Giannis Fikioris , Robert Kleinberg , Yoav Kolumbus , Yishay Mansour , Eva Tardos

While the importance of personalized policymaking is widely recognized, fully personalized implementation remains rare in practice, often due to legal, fairness or cost concerns. We study the problem of policy targeting for a regret-averse…

Econometrics · Economics 2026-04-07 Toru Kitagawa , Sokbae Lee , Chen Qiu

First-price auctions have largely replaced traditional bidding approaches based on Vickrey auctions in programmatic advertising. As far as learning is concerned, first-price auctions are more challenging because the optimal bidding strategy…

Machine Learning · Computer Science 2021-11-23 Juliette Achddou , Olivier Cappé , Aurélien Garivier

The Sliding Window Secretary Problem allows a window of choices to the Classical Secretary Problem, in which there is the option to choose the previous $K$ choices immediately prior to the current choice. We consider a case of this…

Probability · Mathematics 2015-09-01 Shan-Yuan Ho , Abijith Krishnan

Optimising queries in real-world situations under imperfect conditions is still a problem that has not been fully solved. We consider finding the optimal order in which to execute a given set of selection operators under partial ignorance…

Databases · Computer Science 2015-07-30 Khaled H. Alyoubi , Sven Helmer , Peter T. Wood

Motivated by large-market applications such as crowdsourcing, we revisit the problem of budget-feasible mechanism design under a "small-bidder assumption". Anari, Goel, and Nikzad (2018) gave a mechanism that has optimal competitive ratio…

Computer Science and Game Theory · Computer Science 2022-11-17 Aviad Rubinstein , Junyao Zhao