Dana Drachsler Cohen
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who talks about the same things
- Anan Kabaha6 talks
- Aaron Roth11 talks
- Abraham Kang5 talks
- Uri Alon4 talks
- Irina Vidal Migallón7 talks
- Katharine Jarmul25 talks
| title | conference | date |
|---|---|---|
| Guarding the Privacy of Label-Only Access to Neural Network Classifiers via Formal(…) | OOPSLA 2025 | 2025-10-16 |
Claims a practical verifier, LUCID, that computes an iDP-DB overapproximation so noise is added only to inputs that actually risk leaking labels; it encodes… | ||
| Quantization with Guaranteed Floating-Point Neural Network Classifications | OOPSLA 2025 | 2025-10-16 |
CoMPAQt computes a maximal classification-confidence bound using a novel MILP encoding of quantization plus customized linear relaxations and constraints that… | ||
| Mini-Batch Robustness Verification of Deep Neural Networks | OOPSLA 2025 | 2025-10-16 |
BaVerLy is a sound and complete verifier that jointly verifies mini-batches of ε-balls by encoding networks as MILP and grouping inputs with activation-pattern… | ||
| Enhancing Neural Network Robustness via Synthesis of Repair Programs | SAS 2025 | 2025-10-13 |
A stochastic enumerative synthesizer named DefEnSyn generates short repair programs that change a few latent features via simple arithmetic assignments, learns… | ||
| Verification of Neural Networks' Global Robustness | OOPSLA 2024 | 2024-10-20 |
Introduces Delta Global robustness as the minimal confidence margin guaranteeing any input stays correctly classified under a given perturbation, and builds an… | ||
| Verification of Neural Networks’ Local Differential Classification Privacy | VMCAI 2024 | 2024-01-15 |
Defines local differential classification privacy for black-box classifiers and builds Sphynx, an algorithm that predicts an interval-based abstract “hyper… | ||
| Deep Learning Robustness Verification for Few-Pixel Attacks | OOPSLA 2023 | 2023-10-23 |
Introduces Calzone, an L0 robustness verifier that gives sound and complete proofs by converting t-pixel neighborhoods into box (L-inf) queries and using… | ||
| One Pixel Adversarial Attacks via Sketched Programs | PLDI 2023 | 2023-06-17 |
Claims a method called OPPSLA that synthesizes a sketch-based prioritization program to find one-pixel (or few-pixel) adversarial examples for CIFAR-10 and… | ||
| Maximal Robust Neural Network Specifications via Oracle-guided Numerical Optimi... | VMCAI 2023 | 2023-01-15 |
MaRVeL computes maximal non-uniform robust specifications that explicitly maximize a chosen norm by coupling a numerical optimizer with a non-differentiable… | ||
| Config2Spec: Mining Network Specifications from Network Configurations | NSDI 2020 | 2020-02-25 |
Config2Spec automatically synthesizes a formal network specification from device configurations plus a failure model, combining data‑plane analysis and… | ||
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