@inproceedings{58224,
  author       = {{Kenneweg, Philip and Kenneweg, Tristan and Fumagalli, Fabian and Hammer, Barbara}},
  booktitle    = {{2024 International Joint Conference on Neural Networks (IJCNN)}},
  keywords     = {{Training, Schedules, Codes, Search methods, Source coding, Computer architecture, Transformers}},
  pages        = {{1--8}},
  title        = {{{No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation}}},
  doi          = {{10.1109/IJCNN60899.2024.10650124}},
  year         = {{2024}},
}

@inbook{21396,
  abstract     = {{Verifiable random functions (VRFs) are essentially digital signatures with additional properties, namely verifiable uniqueness and pseudorandomness, which make VRFs a useful tool, e.g., to prevent enumeration in DNSSEC Authenticated Denial of Existence and the CONIKS key management system, or in the random committee selection of the Algorand blockchain.

Most standard-model VRFs rely on admissible hash functions (AHFs) to achieve security against adaptive attacks in the standard model. Known AHF constructions are based on error-correcting codes, which yield asymptotically efficient constructions. However, previous works do not clarify how the code should be instantiated concretely in the real world. The rate and the minimal distance of the selected code have significant impact on the efficiency of the resulting cryptosystem, therefore it is unclear if and how the aforementioned constructions can be used in practice.

First, we explain inherent limitations of code-based AHFs. Concretely, we assume that even if we were given codes that achieve the well-known Gilbert-Varshamov or McEliece-Rodemich-Rumsey-Welch bounds, existing AHF-based constructions of verifiable random functions (VRFs) can only be instantiated quite inefficiently. Then we introduce and construct computational AHFs (cAHFs). While classical AHFs are information-theoretic, and therefore work even in presence of computationally unbounded adversaries, cAHFs provide only security against computationally bounded adversaries. However, we show that cAHFs can be instantiated significantly more efficiently. Finally, we use our cAHF to construct the currently most efficient verifiable random function with full adaptive security in the standard model.}},
  author       = {{Jager, Tibor and Niehues, David}},
  booktitle    = {{Lecture Notes in Computer Science}},
  isbn         = {{9783030384708}},
  issn         = {{0302-9743}},
  keywords     = {{Admissible hash functions, Verifiable random functions, Error-correcting codes, Provable security}},
  location     = {{Waterloo, Canada}},
  title        = {{{On the Real-World Instantiability of Admissible Hash Functions and Efficient Verifiable Random Functions}}},
  doi          = {{10.1007/978-3-030-38471-5_13}},
  year         = {{2020}},
}

@inproceedings{11828,
  abstract     = {{In this paper we present a comparison of the recently proposed Soft-Feature Distributed Speech Recognition (SFDSR) with the two evaluated candidate codecs for Speech Enabled Services over wireless networks: Adaptive Multirate Codec (AMR) and the ETSI Extended Advanced Front-End for Distributed Speech Recognition (XAFE). It is shown that SFDSR achieves the best recognition performance on a simulated GSM transmission, followed by XAFE and AMR.We also present some new results concerning SFDSR which demonstrate the versatility of the approach. Further, a simple method is introduced which considerably reduces the computational effort.}},
  author       = {{Ion, Valentin and Haeb-Umbach, Reinhold}},
  booktitle    = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)}},
  keywords     = {{adaptive codes, adaptive multirate codec, AMR, distributed speech recognition, ETSI, extended advanced front-end, recognition performance, SFDSR, simulated GSM transmission, soft-feature distributed speech recognition, speech codecs, speech coding, speech recognition, variable rate codes, XAFE}},
  pages        = {{333--336}},
  title        = {{{A Comparison of Soft-Feature Distributed Speech Recognition with Candidate Codecs for Speech Enabled Mobile Services}}},
  doi          = {{10.1109/ICASSP.2005.1415118}},
  volume       = {{1}},
  year         = {{2005}},
}