◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Nadejda Drenska

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • math.AP2
  • math.OC2

identity via Semantic Scholar / OpenAlex

most citedA PDE Approach to the Prediction of a Binary Sequence with Advice from Two History-Dependent Experts

1 citations · 1 across the 2 of their papers we have counts for

collaborators

4 papers

math.OC2020

Asymptotically optimal strategies for online prediction with history-dependent experts

Jeff Calder, Nadejda Drenska

We establish sharp asymptotically optimal strategies for the problem of online prediction with history dependent experts. The prediction problem is played (in part) over a discrete…

math.AP2020

Online Prediction With History-Dependent Experts: The General Case

Nadejda Drenska, Jeff Calder

We study the problem of prediction of binary sequences with expert advice in the online setting, which is a classic example of online machine learning. We interpret the binary sequ…

math.OC2020★ 1 cited

A PDE Approach to the Prediction of a Binary Sequence with Advice from Two History-Dependent Experts

Nadejda Drenska, Robert V. Kohn

The prediction of a binary sequence is a classic example of online machine learning. We like to call it the 'stock prediction problem,' viewing the sequence as the price history of…

math.AP2019

Prediction with Expert Advice: a PDE Perspective

Nadejda Drenska, Robert V. Kohn

This work addresses a classic problem of online prediction with expert advice. We assume an adversarial opponent, and we consider both the finite-horizon and random-stopping versio…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.