12 papers
Differentiable Weightless Controllers: Learning Logic Circuits for Continuous Control
Fabian Kresse, Christoph H. Lampert
Controlling autonomous systems under real-world conditions often requires policies that can be evaluated with low latency and minimal energy consumption. Unfortunately, these condi…
Learning Quantized Continuous Controllers for Integer Hardware
Fabian Kresse, Christoph H. Lampert
Deploying continuous-control reinforcement learning policies on embedded hardware requires meeting tight latency and power budgets. Small FPGAs can deliver these, but only if costl…
Adaptive Sampling and Clipping for Private Worst-Case Group Optimization
Max Cairney-Leeming, Amartya Sanyal, Christoph H. Lampert
A central requirement for the acceptance of machine learning methods for human-centric tasks is that they should be fair, in the sense that they should work comparably well for ind…
ASIDE: Architectural Separation of Instructions and Data in Language Models
Egor Zverev, Evgenii Kortukov, Alexander Panfilov +5
Despite their remarkable performance, large language models lack elementary safety features, making them susceptible to numerous malicious attacks. In particular, previous work has…
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes
Hossein Zakerinia, Christoph H. Lampert
We present new fast-rate PAC-Bayesian generalization bounds for multi-task and meta-learning in the unbalanced setting, i.e. when the tasks have training sets of different sizes, a…
Logic Gate Neural Networks are Good for Verification
Fabian Kresse, Emily Yu, Christoph H. Lampert +1
Learning-based systems are increasingly deployed across various domains, yet the complexity of traditional neural networks poses significant challenges for formal verification. Unl…