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Robust estimation is much more challenging in high dimensions than it is in one dimension: Most techniques either lead to intractable optimization problems or estimators that can tolerate only a tiny fraction of errors. Recent work in…

Machine Learning · Computer Science 2018-03-14 Ilias Diakonikolas , Gautam Kamath , Daniel M. Kane , Jerry Li , Ankur Moitra , Alistair Stewart

Estimating causal effects under interference is pertinent to many real-world settings. Recent work with low-order potential outcomes models uses a rollout design to obtain unbiased estimators that require no interference network…

Methodology · Statistics 2025-02-12 Mayleen Cortez-Rodriguez , Matthew Eichhorn , Christina Lee Yu

Near-term feasibility, classical hardness, and verifiability are the three requirements for demonstrating quantum advantage; most existing quantum advantage proposals achieve at most two. A promising candidate recently proposed is through…

Quantum Physics · Physics 2025-10-02 Yuxuan Zhang

The hope of the quantum computing field is that quantum architectures are able to scale up and realize fault-tolerant quantum computing. Due to engineering challenges, such ''cheap'' error correction may be decades away. In the meantime, we…

Quantum Physics · Physics 2025-02-17 Rutuja Kshirsagar , Amara Katabarwa , Peter D. Johnson

The problem of reconstructing a sequence of independent and identically distributed symbols from a set of equal size, consecutive, fragments, as well as a dependent reference sequence, is considered. First, in the regime in which the…

Information Theory · Computer Science 2023-07-20 Nir Weinberger , Ilan Shomorony

The security of most existing cryptocurrencies is based on a concept called Proof-of-Work, in which users must solve a computationally hard cryptopuzzle to authorize transactions (`one unit of computation, one vote'). This leads to enormous…

Computer Science and Game Theory · Computer Science 2018-09-19 Jonah Brown-Cohen , Arvind Narayanan , Christos-Alexandros Psomas , S. Matthew Weinberg

As we exhaust methods that reduces variance without introducing bias, reducing variance in experiments often requires accepting some bias, using methods like winsorization or surrogate metrics. While this bias-variance tradeoff can be…

Methodology · Statistics 2025-11-05 Daniel Ting , Kenneth Hung

The occurrence of successive extreme observations can have an impact on society. In extreme value theory there are parameters to evaluate the effect of clustering of high values, such as the extremal index. The estimation of the extremal…

Methodology · Statistics 2021-08-03 Helena Ferreira , Marta Ferreira

Blockchain is a novel technology that is rising a lot of interest in the industrial and re- search sectors because its properties of decentralisation, immutability and data integrity. Initially, the underlying consensus mechanism has been…

Cryptography and Security · Computer Science 2018-05-10 Stefano De Angelis

In a binary classification problem where the goal is to fit an accurate predictor, the presence of corrupted labels in the training data set may create an additional challenge. However, in settings where likelihood maximization is poorly…

Statistics Theory · Mathematics 2021-06-18 Yonghoon Lee , Rina Foygel Barber

Rerandomization is a modern experimental design technique that repeatedly randomizes treatment assignments until covariates are deemed balanced between treatment groups. This enhances the precision and coherence of causal effect estimators,…

Methodology · Statistics 2025-12-08 Antônio Carlos Herling Ribeiro Junior , Zach Branson

People often deviate from expected utility theory when making risky and intertemporal choices. While the effects of probabilistic risk and time delay have been extensively studied in isolation, their interplay and underlying theoretical…

Theoretical Economics · Economics 2025-04-10 Ho Ka Chan , Taro Toyoizumi

Blockchains have become immensely popular and are high on the list of national and international research and innovation agenda's. This is partly caused by the numerous interesting applications, combined with the promise of full…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-03 Maarten van Steen , Andrew Chien , Patrick Eugster

Randomization is a common technique used in clinical trials to eliminate potential bias and confounders in a patient population. Equal allocation to treatment groups is the standard due to its optimal efficiency in many cases. However, in…

Applications · Statistics 2020-04-09 Thevaa Chandereng , Xiaodan Wei , Rick Chappell

The research area of algorithms with predictions has seen recent success showing how to incorporate machine learning into algorithm design to improve performance when the predictions are correct, while retaining worst-case guarantees when…

Machine Learning · Computer Science 2022-12-06 Michael Dinitz , Sungjin Im , Thomas Lavastida , Benjamin Moseley , Sergei Vassilvitskii

Tests for proportional hazards assumption concerning specified covariates or groups of covariates are proposed. The class of alternatives is wide: log-hazard rates under different values of covariates may cross, approach, go away. The data…

Statistics Theory · Mathematics 2020-01-20 Vilijandas Bagdonavičius , Rūta Levulienė

Bias is known to be an impediment to fair decisions in many domains such as human resources, the public sector, health care etc. Recently, hope has been expressed that the use of machine learning methods for taking such decisions would…

Machine Learning · Computer Science 2019-09-05 Jindong Gu , Daniela Oelke

We study the design of mechanisms -- e.g., auctions -- when the designer does not control information flows between mechanism participants. A mechanism equilibrium is leakage-proof if no player conditions their actions on leaked…

Theoretical Economics · Economics 2025-11-04 Samuel Häfner , Marek Pycia , Haoyuan Zeng

State of the art quantum computing architectures are founded on the decision to use scalable but faulty quantum hardware in conjunction with an efficient error correcting code capable of tolerating high error rates. The promised effect of…

Quantum Physics · Physics 2021-08-23 Alexandru Paler , Austin G. Fowler , Robert Wille

Interference arises when an individual's potential outcome depends on the individual treatment level, but also on the treatment level of others. A common assumption in the causal inference literature in the presence of interference is…

Methodology · Statistics 2018-05-15 Georgia Papadogeorgou , Fabrizia Mealli , Corwin M. Zigler
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