Timezone: »
Uncertainty sampling in active learning is heavily used in practice to reduce the annotation cost. However, there has been no wide consensus on the function to be used for uncertainty estimation in binary classification tasks and convergence guarantees of the corresponding active learning algorithms are not well understood. The situation is even more challenging for multi-category classification. In this work, we propose an efficient uncertainty estimator for binary classification which we also extend to multiple classes, and provide a non-asymptotic rate of convergence for our uncertainty sampling based active learning algorithm in both cases under no-noise conditions (i.e., linearly separable data). We also extend our analysis to the noisy case and provide theoretical guarantees for our algorithm under the influence of noise in the task of binary and multi-class classification.
Author Information
Anant Raj (INRIA- ENS and UIUC)
Marie-Curie Fellow
Francis Bach (INRIA - Ecole Normale Supérieure)
Related Events (a corresponding poster, oral, or spotlight)
-
2022 Spotlight: Convergence of Uncertainty Sampling for Active Learning »
Wed. Jul 20th 06:25 -- 06:30 PM Room Ballroom 3 & 4
More from the Same Authors
-
2023 : Differentiable Clustering and Partial Fenchel-Young Losses »
Lawrence Stewart · Francis Bach · Felipe Llinares-Lopez · Quentin Berthet -
2023 Poster: Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions »
Anant Raj · Lingjiong Zhu · Mert Gurbuzbalaban · Umut Simsekli -
2023 Poster: On Bridging the Gap between Mean Field and Finite Width Deep Random Multilayer Perceptron with Batch Normalization »
Amir Joudaki · Hadi Daneshmand · Francis Bach -
2023 Poster: Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy »
Blake Woodworth · Konstantin Mishchenko · Francis Bach -
2022 Poster: Anticorrelated Noise Injection for Improved Generalization »
Antonio Orvieto · Hans Kersting · Frank Proske · Francis Bach · Aurelien Lucchi -
2022 Spotlight: Anticorrelated Noise Injection for Improved Generalization »
Antonio Orvieto · Hans Kersting · Frank Proske · Francis Bach · Aurelien Lucchi -
2021 Poster: Disambiguation of Weak Supervision leading to Exponential Convergence rates »
Vivien Cabannnes · Francis Bach · Alessandro Rudi -
2021 Spotlight: Disambiguation of Weak Supervision leading to Exponential Convergence rates »
Vivien Cabannnes · Francis Bach · Alessandro Rudi -
2020 : Q&A with Francis Bach »
Francis Bach -
2020 : Talk by Francis Bach - Second Order Strikes Back - Globally convergent Newton methods for ill-conditioned generalized self-concordant Losses »
Francis Bach -
2020 Poster: Stochastic Optimization for Regularized Wasserstein Estimators »
Marin Ballu · Quentin Berthet · Francis Bach -
2020 Poster: Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization »
Hadrien Hendrikx · Lin Xiao · Sebastien Bubeck · Francis Bach · Laurent Massoulié -
2020 Poster: Consistent Structured Prediction with Max-Min Margin Markov Networks »
Alex Nowak · Francis Bach · Alessandro Rudi -
2020 Poster: Structured Prediction with Partial Labelling through the Infimum Loss »
Vivien Cabannnes · Alessandro Rudi · Francis Bach -
2020 Poster: A simpler approach to accelerated optimization: iterative averaging meets optimism »
Pooria Joulani · Anant Raj · Andras Gyorgy · Csaba Szepesvari -
2019 Invited Talk: Online Dictionary Learning for Sparse Coding »
Julien Mairal · Francis Bach · Jean Ponce · Guillermo Sapiro -
2018 Poster: On Matching Pursuit and Coordinate Descent »
Francesco Locatello · Anant Raj · Sai Praneeth Reddy Karimireddy · Gunnar Ratsch · Bernhard Schölkopf · Sebastian Stich · Martin Jaggi -
2018 Oral: On Matching Pursuit and Coordinate Descent »
Francesco Locatello · Anant Raj · Sai Praneeth Reddy Karimireddy · Gunnar Ratsch · Bernhard Schölkopf · Sebastian Stich · Martin Jaggi -
2017 Poster: Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks »
Kevin Scaman · Francis Bach · Sebastien Bubeck · Yin Tat Lee · Laurent Massoulié -
2017 Talk: Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks »
Kevin Scaman · Francis Bach · Sebastien Bubeck · Yin Tat Lee · Laurent Massoulié -
2017 Poster: Approximate Steepest Coordinate Descent »
Sebastian Stich · Anant Raj · Martin Jaggi -
2017 Talk: Approximate Steepest Coordinate Descent »
Sebastian Stich · Anant Raj · Martin Jaggi