ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1905.11063
  4. Cited By
Dataset2Vec: Learning Dataset Meta-Features

Dataset2Vec: Learning Dataset Meta-Features

27 May 2019
H. Jomaa
Lars Schmidt-Thieme
Josif Grabocka
    SSL
ArXivPDFHTML

Papers citing "Dataset2Vec: Learning Dataset Meta-Features"

15 / 15 papers shown
Title
Data Analysis Prediction over Multiple Unseen Datasets: A Vector Embedding Approach
Data Analysis Prediction over Multiple Unseen Datasets: A Vector Embedding Approach
Andreas Loizou
Dimitrios Tsoumakos
45
0
0
24 Feb 2025
Multi-Robot Motion Planning with Diffusion Models
Multi-Robot Motion Planning with Diffusion Models
Yorai Shaoul
Itamar Mishani
Shivam Vats
Jiaoyang Li
Maxim Likhachev
DiffM
53
6
0
04 Oct 2024
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Sebastian Pineda Arango
Fabio Ferreira
Arlind Kadra
Frank Hutter
Frank Hutter Josif Grabocka
44
15
0
06 Jun 2023
Deep Ranking Ensembles for Hyperparameter Optimization
Deep Ranking Ensembles for Hyperparameter Optimization
Abdus Salam Khazi
Sebastian Pineda Arango
Josif Grabocka
BDL
44
7
0
27 Mar 2023
Improving Hyperparameter Optimization by Planning Ahead
Improving Hyperparameter Optimization by Planning Ahead
H. Jomaa
Jonas K. Falkner
Lars Schmidt-Thieme
22
0
0
15 Oct 2021
HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on
  OpenML
HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML
Sebastian Pineda Arango
H. Jomaa
Martin Wistuba
Josif Grabocka
29
55
0
11 Jun 2021
What to Pre-Train on? Efficient Intermediate Task Selection
What to Pre-Train on? Efficient Intermediate Task Selection
Clifton A. Poth
Jonas Pfeiffer
Andreas Rucklé
Iryna Gurevych
24
95
0
16 Apr 2021
Learning Abstract Task Representations
Learning Abstract Task Representations
Mikhail M. Meskhi
A. Rivolli
R. G. Mantovani
R. Vilalta
30
7
0
19 Jan 2021
Weighted Meta-Learning
Weighted Meta-Learning
Diana Cai
Rishit Sheth
Lester W. Mackey
Nicolò Fusi
39
12
0
20 Mar 2020
LEEP: A New Measure to Evaluate Transferability of Learned
  Representations
LEEP: A New Measure to Evaluate Transferability of Learned Representations
Cuong V Nguyen
Tal Hassner
Matthias Seeger
Cédric Archambeau
28
213
0
27 Feb 2020
HIDRA: Head Initialization across Dynamic targets for Robust
  Architectures
HIDRA: Head Initialization across Dynamic targets for Robust Architectures
Rafael Rêgo Drumond
L. Brinkmeyer
Josif Grabocka
Lars Schmidt-Thieme
21
4
0
28 Oct 2019
Chameleon: Learning Model Initializations Across Tasks With Different
  Schemas
Chameleon: Learning Model Initializations Across Tasks With Different Schemas
L. Brinkmeyer
Rafael Rêgo Drumond
Randolf Scholz
Josif Grabocka
Lars Schmidt-Thieme
CLL
19
8
0
30 Sep 2019
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCV
BDL
231
500
0
11 Jun 2018
Probabilistic Model-Agnostic Meta-Learning
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn
Kelvin Xu
Sergey Levine
BDL
178
666
0
07 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
493
11,727
0
09 Mar 2017
1