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- Ulrich Rührmair, Frank Sehnke, Jan Sölter, Gideon Dror, Srinivas Devadas, Jürgen Schmidhuber
- ACM Conference on Computer and Communications…
- 2010

We show in this paper how several proposed Physical Unclonable Functions (PUFs) can be broken by numerical modeling attacks. Given a set of challenge-response pairs (CRPs) of a PUF, our attacks construct a computer algorithm which behaves indistinguishably from the original PUF on almost all CRPs. This algorithm can subsequently impersonate the PUF, and can… (More)

- Ulrich Rührmair, Jan Sölter, +7 authors Srinivas Devadas
- IEEE Transactions on Information Forensics and…
- 2013

We discuss numerical modeling attacks on several proposed strong physical unclonable functions (PUFs). Given a set of challenge-response pairs (CRPs) of a Strong PUF, the goal of our attacks is to construct a computer algorithm which behaves indistinguishably from the original PUF on almost all CRPs. If successful, this algorithm can subsequently… (More)

- Frank Sehnke, Christian Osendorfer, Thomas Rückstieß, Alex Graves, Jan Peters, Jürgen Schmidhuber
- Neural Networks
- 2010

We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in parameter space, which leads to lower variance gradient estimates than obtained by regular policy gradient methods. We show that for several complex control tasks, including robust… (More)

- Ulrich Rührmair, Jan Sölter, Frank Sehnke
- IACR Cryptology ePrint Archive
- 2009

We investigate the foundations of Physical Unclonable Functions from several perspectives. Firstly, we discuss formal and conceptual issues in the various current definitions of PUFs. As we argue, they have the effect that many PUF candidates formally meet no existing definition. Next, we present alternative definitions and a new formalism. It avoids… (More)

- Tom Schaul, Justin Bayer, +5 authors Jürgen Schmidhuber
- Journal of Machine Learning Research
- 2010

PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easyto-use yet still powerful algorithms for machine learning tasks, including a variety of predefined environments and benchmarks to test and compare algorithms. Implemented algorithms include Long Short-Term Memory (LSTM), policy gradient methods,… (More)

- Thomas Rückstieß, Frank Sehnke, Tom Schaul, Daan Wierstra, Yi Sun, Jürgen Schmidhuber
- Paladyn
- 2010

This paper discusses parameter-based exploration methods for reinforcement learning. Parameter-based methods perturb parameters of a general function approximator directly, rather than adding noise to the resulting actions. Parameter-based exploration unifies reinforcement learning and black-box optimization, and has several advantages over action… (More)

We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in parameter space, which leads to lower variance gradient estimates than those obtained by policy gradient methods such as REINFORCE. For several complex control tasks, including robust… (More)

- Patrick Heinemann, Frank Sehnke, Felix Streichert, Andreas Zell
- RoboCup
- 2006

Many approaches for object detection based on color coding were published in the RoboCup domain. They are tuned to the typical RoboCup scenario of constant lighting using a static subdivision of the color space. However, such algorithms will soon be of limited use, when playing under changing and finally natural lighting. This paper presents an algorithm… (More)

- Patrick Heinemann, Felix Streichert, Frank Sehnke, Andreas Zell
- IEEE Congress on Evolutionary Computation
- 2006

A common practical problem in mobile robotics is the task to calibrate the robot’s sensors. Although, the general mapping of the sensor data to robot-centered world coordinates is given by the hardware configuration, the parameters of this mapping vary even between robots with the same configuration. In the RoboCup domain, these parameters can change… (More)

- Jakob Engel, Markus Holzer, Oliver Ruepp, Frank Sehnke
- FUN
- 2012

The crossword puzzle is a classic pastime that is well-known all over the world. We consider the crossword manufacturing process in more detail, investigating a two-step approach, first generating a mask, which is an empty crossword puzzle skeleton, and then filling the mask with words from a given dictionary to obtain a valid crossword. We show that the… (More)