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ORCIDMislav Balunovic
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2020 – today
- 2024
[c19]Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev:
Beyond Memorization: Violating Privacy via Inference with Large Language Models. ICLR 2024- [c18]Mark Vero, Mislav Balunovic, Martin T. Vechev:
CuTS: Customizable Tabular Synthetic Data Generation. ICML 2024 - [c17]Robin Staab, Nikola Jovanovic, Mislav Balunovic, Martin T. Vechev:
From Principle to Practice: Vertical Data Minimization for Machine Learning. SP 2024: 4733-4752 - [i17]Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev:
Large Language Models are Advanced Anonymizers. CoRR abs/2402.13846 (2024) - [i16]Edoardo Debenedetti, Jie Zhang, Mislav Balunovic, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr:
AgentDojo: A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents. CoRR abs/2406.13352 (2024) - 2023
- [c16]Nikola Jovanovic, Mislav Balunovic, Dimitar Iliev Dimitrov, Martin T. Vechev:
FARE: Provably Fair Representation Learning with Practical Certificates. ICML 2023: 15401-15420 - [c15]Mark Vero, Mislav Balunovic, Dimitar Iliev Dimitrov, Martin T. Vechev:
TabLeak: Tabular Data Leakage in Federated Learning. ICML 2023: 35051-35083 - [i15]Mark Vero, Mislav Balunovic, Martin T. Vechev:
Programmable Synthetic Tabular Data Generation. CoRR abs/2307.03577 (2023) - [i14]Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev:
Beyond Memorization: Violating Privacy Via Inference with Large Language Models. CoRR abs/2310.07298 (2023) - [i13]Robin Staab, Nikola Jovanovic, Mislav Balunovic, Martin T. Vechev:
From Principle to Practice: Vertical Data Minimization for Machine Learning. CoRR abs/2311.10500 (2023) - 2022
- [j2]Dimitar Iliev Dimitrov, Mislav Balunovic, Nikola Konstantinov, Martin T. Vechev:
Data Leakage in Federated Averaging. Trans. Mach. Learn. Res. 2022 (2022) - [j1]Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev:
On the Paradox of Certified Training. Trans. Mach. Learn. Res. 2022 (2022) - [c14]Momchil Peychev
, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev:
Latent Space Smoothing for Individually Fair Representations. ECCV (13) 2022: 535-554 - [c13]Mislav Balunovic, Dimitar Iliev Dimitrov, Robin Staab, Martin T. Vechev:
Bayesian Framework for Gradient Leakage. ICLR 2022 - [c12]Mislav Balunovic, Anian Ruoss, Martin T. Vechev:
Fair Normalizing Flows. ICLR 2022 - [c11]Mislav Balunovic, Dimitar I. Dimitrov, Nikola Jovanovic, Martin T. Vechev:
LAMP: Extracting Text from Gradients with Language Model Priors. NeurIPS 2022 - [i12]Dimitar I. Dimitrov, Mislav Balunovic, Nikola Jovanovic, Martin T. Vechev:
LAMP: Extracting Text from Gradients with Language Model Priors. CoRR abs/2202.08827 (2022) - [i11]Dimitar I. Dimitrov, Mislav Balunovic, Nikola Konstantinov, Martin T. Vechev:
Data Leakage in Federated Averaging. CoRR abs/2206.12395 (2022) - [i10]Mark Vero, Mislav Balunovic, Dimitar I. Dimitrov, Martin T. Vechev:
Data Leakage in Tabular Federated Learning. CoRR abs/2210.01785 (2022) - [i9]Nikola Jovanovic, Mislav Balunovic, Dimitar I. Dimitrov, Martin T. Vechev:
FARE: Provably Fair Representation Learning. CoRR abs/2210.07213 (2022) - 2021
- [c10]Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev:
Efficient Certification of Spatial Robustness. AAAI 2021: 2504-2513 - [c9]Wonryong Ryou, Jiayu Chen, Mislav Balunovic, Gagandeep Singh, Andrei Marian Dan, Martin T. Vechev:
Scalable Polyhedral Verification of Recurrent Neural Networks. CAV (1) 2021: 225-248 - [c8]Tobias Lorenz, Anian Ruoss, Mislav Balunovic, Gagandeep Singh, Martin T. Vechev:
Robustness Certification for Point Cloud Models. ICCV 2021: 7588-7598 - [c7]Mark Niklas Müller, Mislav Balunovic, Martin T. Vechev:
Certify or Predict: Boosting Certified Robustness with Compositional Architectures. ICLR 2021 - [i8]Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev:
Certified Defenses: Why Tighter Relaxations May Hurt Training? CoRR abs/2102.06700 (2021) - [i7]Tobias Lorenz, Anian Ruoss, Mislav Balunovic, Gagandeep Singh, Martin T. Vechev:
Robustness Certification for Point Cloud Models. CoRR abs/2103.16652 (2021) - [i6]Mislav Balunovic, Anian Ruoss, Martin T. Vechev:
Fair Normalizing Flows. CoRR abs/2106.05937 (2021) - [i5]Mislav Balunovic, Dimitar I. Dimitrov, Robin Staab, Martin T. Vechev:
Bayesian Framework for Gradient Leakage. CoRR abs/2111.04706 (2021) - [i4]Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev:
Latent Space Smoothing for Individually Fair Representations. CoRR abs/2111.13650 (2021) - 2020
- [c6]Mislav Balunovic, Martin T. Vechev:
Adversarial Training and Provable Defenses: Bridging the Gap. ICLR 2020 - [c5]Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin T. Vechev:
Learning Certified Individually Fair Representations. NeurIPS 2020 - [i3]Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin T. Vechev:
Learning Certified Individually Fair Representations. CoRR abs/2002.10312 (2020) - [i2]Wonryong Ryou, Jiayu Chen, Mislav Balunovic, Gagandeep Singh, Andrei Marian Dan, Martin T. Vechev:
Fast and Effective Robustness Certification for Recurrent Neural Networks. CoRR abs/2005.13300 (2020) - [i1]Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev:
Efficient Certification of Spatial Robustness. CoRR abs/2009.09318 (2020)
2010 – 2019
- 2019
- [c4]Jingxuan He, Mislav Balunovic, Nodar Ambroladze, Petar Tsankov, Martin T. Vechev:
Learning to Fuzz from Symbolic Execution with Application to Smart Contracts. CCS 2019: 531-548 - [c3]Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin T. Vechev:
DL2: Training and Querying Neural Networks with Logic. ICML 2019: 1931-1941 - [c2]Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin T. Vechev:
Certifying Geometric Robustness of Neural Networks. NeurIPS 2019: 15287-15297 - 2018
- [c1]Mislav Balunovic, Pavol Bielik, Martin T. Vechev:
Learning to Solve SMT Formulas. NeurIPS 2018: 10338-10349
Coauthor Index
aka: Dimitar Iliev Dimitrov
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last updated on 2024-10-07 22:12 CEST by the dblp team
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