ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2210.03822
  4. Cited By
Is margin all you need? An extensive empirical study of active learning
  on tabular data

Is margin all you need? An extensive empirical study of active learning on tabular data

7 October 2022
Dara Bahri
Heinrich Jiang
Tal Schuster
Afshin Rostamizadeh
    LMTD
ArXiv (abs)PDFHTML

Papers citing "Is margin all you need? An extensive empirical study of active learning on tabular data"

10 / 10 papers shown
Title
Survey of Active Learning Hyperparameters: Insights from a Large-Scale Experimental Grid
Survey of Active Learning Hyperparameters: Insights from a Large-Scale Experimental Grid
Julius Gonsior
Tim Rieß
Anja Reusch
Claudio Hartmann
Maik Thiele
Wolfgang Lehner
169
0
0
04 Jun 2025
No Free Lunch in Active Learning: LLM Embedding Quality Dictates Query Strategy Success
No Free Lunch in Active Learning: LLM Embedding Quality Dictates Query Strategy Success
Lukas Rauch
Moritz Wirth
Denis Huseljic
M. Herde
Bernhard Sick
Yi Men
75
0
0
18 May 2025
Core-Set Selection for Data-efficient Land Cover Segmentation
Core-Set Selection for Data-efficient Land Cover Segmentation
Keiller Nogueira
Akram Zaytar
Wanli Ma
R. Roscher
Ronny Hansch
...
Simone Fobi Nsutezo
Rahul Dodhia
J. L. Ferres
Oktay Karakuş
Paul L. Rosin
176
1
0
02 May 2025
A Cross-Domain Benchmark for Active Learning
A Cross-Domain Benchmark for Active LearningNeural Information Processing Systems (NeurIPS), 2024
M. M. Kholoosi
M. A. Babar
Ilia Koloiarov
Lars Schmidt-Thieme
132
7
0
01 Aug 2024
ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data
ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data
Valentin Margraf
Marcel Wever
Sandra Gilhuber
Gabriel Marques Tavares
Thomas Seidl
Eyke Hüllermeier
165
3
0
25 Jun 2024
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active
  Image Classification
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification
Denis Huseljic
Paul Hahn
M. Herde
Lukas Rauch
Bernhard Sick
206
3
0
13 Apr 2024
Benchmarking Multi-Domain Active Learning on Image Classification
Benchmarking Multi-Domain Active Learning on Image Classification
Jiayi Li
Rohan Taori
Tatsunori Hashimoto
VLM
126
0
0
01 Dec 2023
Generalized Power Attacks against Crypto Hardware using Long-Range Deep
  Learning
Generalized Power Attacks against Crypto Hardware using Long-Range Deep Learning
Elie Bursztein
Luca Invernizzi
Karel Král
D. Moghimi
J. Picod
Marina Zhang
AAML
118
8
0
12 Jun 2023
Combining Self-labeling with Selective Sampling
Combining Self-labeling with Selective Sampling
Jędrzej Kozal
Michal Wo'zniak
95
3
0
11 Jan 2023
Efficient Bayesian Updates for Deep Learning via Laplace Approximations
Efficient Bayesian Updates for Deep Learning via Laplace Approximations
Denis Huseljic
M. Herde
Lukas Rauch
Paul Hahn
Zhixin Huang
D. Kottke
S. Vogt
Bernhard Sick
BDL
171
0
0
12 Oct 2022
1