works on

From the 1 of 19 linked papers with an AI index.

activity
20242026
collaborators

19 papers

cs.GT2026

From Compensation Design to Budget-Feasible Mechanisms: A Constant Approximation for Subadditive Valuations

Ioannis Anagnostides, Kshipra Bhawalkar, Christopher Liaw +3

Budget-feasible mechanism design is a classic framework introduced by Singer, but there is still a wide gap between existing upper and lower bounds. In this paper, we significantly…

cs.DS2026

Learning Distributions from Multiple Data Providers

Jon Kleinberg, Amin Saberi, Xizhi Tan +1

Motivated by learning from heterogeneous and overlapping data providers, we study a stylized model of distribution learning from restricted conditional samples. The goal is to lear…

cs.GT2026

Compensation Design

Ioannis Anagnostides, Kshipra Bhawalkar, Christopher Liaw +5

The paper defines the problem of compensation design, proposing simple cost‑oblivious payment rules that guarantee the existence of pure Nash equilibria with a price of anarchy clo…

cs.DS2026

On Language Generation in the Limit with Bounded Memory

Jon Kleinberg, Anay Mehrotra, Amin Saberi +1

We study language generation in the limit under bounded memory. In this task, a learner observes examples from an unknown target language one at a time and must eventually output o…

stat.ML2026

What is Learnable in Valiant's Theory of the Learnable?

Steve Hanneke, Anay Mehrotra, Grigoris Velegkas +1

Valiant's 1984 paper is widely credited with introducing the PAC learning model, but it, in fact, introduced a different model: unlike PAC learning, the learner receives only posit…

cs.LG2026

On the Learning Curves of Revenue Maximization

Steve Hanneke, Alkis Kalavasis, Shay Moran +1

Learning curves are a fundamental primitive in supervised learning, describing how an algorithm's performance improves with more data and providing a quantitative measure of its ge…