Gintare Karolina Dziugaite
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
21
Venues
6
Active years
2015–2025
Best venue rank
A*
Where they publish
Papers
21 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AISTATS | The Size of Teachers as a Measure of Data Complexity: PAC-Bayes Excess Risk Bounds and Scaling Laws. | Gintare Karolina Dziugaite, Daniel M. Roy |
| 2025 | ICLR | The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws. | Tian Jin, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan Alistarh, Gintare Karolina Dziugaite |
| 2025 | ICLR | Selective Unlearning via Representation Erasure Using Domain Adversarial Training. | Nazanin Mohammadi Sepahvand, Eleni Triantafillou, Hugo Larochelle, Doina Precup, James J. Clark, Daniel M. Roy, Gintare Karolina Dziugaite |
| 2025 | ICML | Mechanistic Unlearning: Robust Knowledge Unlearning and Editing via Mechanistic Localization. | Phillip Guo, Aaquib Syed, Abhay Sheshadri, Aidan Ewart, Gintare Karolina Dziugaite |
| 2025 | ICML | Leveraging Per-Instance Privacy for Machine Unlearning. | Nazanin Mohammadi Sepahvand, Anvith Thudi, Berivan Isik, Ashmita Bhattacharyya, Nicolas Papernot, Eleni Triantafillou, Daniel M. Roy, Gintare Karolina Dziugaite |
| 2024 | AISTATS | Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias. | Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman |
| 2024 | ICLR | The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning. | Tian Jin, Nolan Clement, Xin Dong, Vaishnavh Nagarajan, Michael Carbin, Jonathan Ragan-Kelley, Gintare Karolina Dziugaite |
| 2024 | ICML | Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing. | Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy |
| 2024 | ICML | Mixtures of Experts Unlock Parameter Scaling for Deep RL. | Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro |
| 2023 | ALT | Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization. | Mahdi Haghifam, Borja Rodrguez Glvez, Ragnar Thobaben, Mikael Skoglund, Daniel M. Roy, Gintare Karolina Dziugaite |
| 2023 | ICLR | Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? | Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite |
| 2022 | ISIT | Understanding Generalization via Leave-One-Out Conditional Mutual Information. | Mahdi Haghifam, Shay Moran, Daniel M. Roy, Gintare Karolina Dziugaite |
| 2021 | AISTATS | On the role of data in PAC-Bayes. | Gintare Karolina Dziugaite, Kyle Hsu, Waseem Gharbieh, Gabriel Arpino, Daniel M. Roy |
| 2021 | ICLR | Pruning Neural Networks at Initialization: Why Are We Missing the Mark? | Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin |
| 2020 | AISTATS | RelatIF: Identifying Explanatory Training Samples via Relative Influence. | Elnaz Barshan, Marc-Etienne Brunet, Gintare Karolina Dziugaite |
| 2020 | AISTATS | Stochastic Neural Network with Kronecker Flow. | Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville |
| 2020 | ICML | Linear Mode Connectivity and the Lottery Ticket Hypothesis. | Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin |
| 2020 | ICML | In Defense of Uniform Convergence: Generalization via Derandomization with an Application to Interpolating Predictors. | Jeffrey Negrea, Gintare Karolina Dziugaite, Daniel M. Roy |
| 2018 | ICML | Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors. | Gintare Karolina Dziugaite, Daniel M. Roy |
| 2017 | UAI | Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data. | Gintare Karolina Dziugaite, Daniel M. Roy |
| 2015 | UAI | Training generative neural networks via Maximum Mean Discrepancy optimization. | Gintare Karolina Dziugaite, Daniel M. Roy, Zoubin Ghahramani |