Mislav Balunovic

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 36

Top Topics

Top Venues

Publications

Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
Beyond Memorization: Violating Privacy via Inference with Large Language Models. ICLR (2024)
Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
Large Language Models are Advanced Anonymizers. CoRR (2024)
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 (2024)
Mark Vero, Mislav Balunovic, Martin T. Vechev
Programmable Synthetic Tabular Data Generation. CoRR (2023)
Robin Staab, Nikola Jovanovic, Mislav Balunovic, Martin T. Vechev
From Principle to Practice: Vertical Data Minimization for Machine Learning. CoRR (2023)
Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
Beyond Memorization: Violating Privacy Via Inference with Large Language Models. CoRR (2023)
Mark Vero, Mislav Balunovic, Dimitar Iliev Dimitrov, Martin T. Vechev
TabLeak: Tabular Data Leakage in Federated Learning. ICML (2023)
Nikola Jovanovic, Mislav Balunovic, Dimitar Iliev Dimitrov, Martin T. Vechev
FARE: Provably Fair Representation Learning with Practical Certificates. ICML (2023)
Mislav Balunovic, Dimitar I. Dimitrov, Nikola Jovanovic, Martin T. Vechev
LAMP: Extracting Text from Gradients with Language Model Priors. NeurIPS (2022)
Mislav Balunovic, Dimitar Iliev Dimitrov, Robin Staab, Martin T. Vechev
Bayesian Framework for Gradient Leakage. ICLR (2022)
Dimitar Iliev Dimitrov, Mislav Balunovic, Nikola Konstantinov, Martin T. Vechev
Data Leakage in Federated Averaging. Trans. Mach. Learn. Res. 2022 (2022)
Mark Vero, Mislav Balunovic, Dimitar I. Dimitrov, Martin T. Vechev
Data Leakage in Tabular Federated Learning. CoRR (2022)
Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
On the Paradox of Certified Training. Trans. Mach. Learn. Res. 2022 (2022)
Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
Latent Space Smoothing for Individually Fair Representations. ECCV (13) (2022)
Dimitar I. Dimitrov, Mislav Balunovic, Nikola Konstantinov, Martin T. Vechev
Data Leakage in Federated Averaging. CoRR (2022)
Dimitar I. Dimitrov, Mislav Balunovic, Nikola Jovanovic, Martin T. Vechev
LAMP: Extracting Text from Gradients with Language Model Priors. CoRR (2022)
Mislav Balunovic, Anian Ruoss, Martin T. Vechev
Fair Normalizing Flows. ICLR (2022)
Nikola Jovanovic, Mislav Balunovic, Dimitar I. Dimitrov, Martin T. Vechev
FARE: Provably Fair Representation Learning. CoRR (2022)
Tobias Lorenz, Anian Ruoss, Mislav Balunovic, Gagandeep Singh, Martin T. Vechev
Robustness Certification for Point Cloud Models. CoRR (2021)
Mislav Balunovic, Dimitar I. Dimitrov, Robin Staab, Martin T. Vechev
Bayesian Framework for Gradient Leakage. CoRR (2021)
Mark Niklas Müller, Mislav Balunovic, Martin T. Vechev
Certify or Predict: Boosting Certified Robustness with Compositional Architectures. ICLR (2021)
Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
Efficient Certification of Spatial Robustness. AAAI (2021)
Tobias Lorenz, Anian Ruoss, Mislav Balunovic, Gagandeep Singh, Martin T. Vechev
Robustness Certification for Point Cloud Models. ICCV (2021)
Wonryong Ryou, Jiayu Chen, Mislav Balunovic, Gagandeep Singh, Andrei Marian Dan, Martin T. Vechev
Scalable Polyhedral Verification of Recurrent Neural Networks. CAV (1) (2021)
Mislav Balunovic, Anian Ruoss, Martin T. Vechev
Fair Normalizing Flows. CoRR (2021)
Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
Certified Defenses: Why Tighter Relaxations May Hurt Training? CoRR (2021)
Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
Latent Space Smoothing for Individually Fair Representations. CoRR (2021)
Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
Efficient Certification of Spatial Robustness. CoRR (2020)
Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin T. Vechev
Learning Certified Individually Fair Representations. NeurIPS (2020)
Wonryong Ryou, Jiayu Chen, Mislav Balunovic, Gagandeep Singh, Andrei Marian Dan, Martin T. Vechev
Fast and Effective Robustness Certification for Recurrent Neural Networks. CoRR (2020)
Mislav Balunovic, Martin T. Vechev
Adversarial Training and Provable Defenses: Bridging the Gap. ICLR (2020)
Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin T. Vechev
Learning Certified Individually Fair Representations. CoRR (2020)
Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin T. Vechev
DL2: Training and Querying Neural Networks with Logic. ICML (2019)
Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin T. Vechev
Certifying Geometric Robustness of Neural Networks. NeurIPS (2019)
Jingxuan He, Mislav Balunovic, Nodar Ambroladze, Petar Tsankov, Martin T. Vechev
Learning to Fuzz from Symbolic Execution with Application to Smart Contracts. CCS (2019)
Mislav Balunovic, Pavol Bielik, Martin T. Vechev
Learning to Solve SMT Formulas. NeurIPS (2018)