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pro vyhledávání: '"A. Sreejith"'
In this paper, we introduce a novel method for active learning of deterministic real-time one-counter automata (DROCA). The existing techniques for learning DROCA rely on observing the behaviour of the DROCA up to exponentially large counter-values.
Externí odkaz:
http://arxiv.org/abs/2411.08815
Autor:
Purkait, Suvankar, Maiti, Tanmay, Agarwal, Pooja, Sahoo, Suparna, J., Sreejith G., Das, Sourin, Biasiol, Giorgio, Sorba, Lucia, Karmakar, Biswajit
Edge reconstruction of gate-tunable compressible quantum Hall fluids in the filling fraction range 1/3 to 2/3 is studied by measuring transmitted conductance of two individually excited fractional $e^2/3h$ edge modes of bulk 2/3 fractional quantum Ha
Externí odkaz:
http://arxiv.org/abs/2411.06840
Autor:
Yang, Yifei, Nair, Sreejith, Fan, Yihong, Chen, Yu-Chia, Jia, Qi, Benally, Onri Jay, Lee, Seungjun, Jeong, Seung Gyo, Yang, Zhifei, Low, Tony, Jalan, Bharat, Wang, Jian-Ping
Crystal symmetry plays an important role in the Hall effects. Unconventional spin Hall effect (USHE), characterized by Dresselhaus and out-of-plane spins, has been observed in materials with low crystal symmetry. Recently, antisymmetric planar Hall e
Externí odkaz:
http://arxiv.org/abs/2411.05688
This paper introduces deterministic weighted real-time one-counter automaton (DWROCA). A DWROCA is a deterministic real-time one-counter automaton whose transitions are assigned a weight from a field. Two DWROCAs are equivalent if every word accepted
Externí odkaz:
http://arxiv.org/abs/2411.03066
Autor:
Kapu, Nirmal Joshua, Sreejith, Mihit
Generating executable code from natural language instructions using Large Language Models (LLMs) poses challenges such as semantic ambiguity and understanding taskspecific contexts. To address these issues, we propose a system called DemoCraft, which
Externí odkaz:
http://arxiv.org/abs/2411.00865
Autor:
Volnova, Alina A., Aleo, Patrick D., Lavrukhina, Anastasia, Russeil, Etienne, Semenikhin, Timofey, Gangler, Emmanuel, Ishida, Emille E. O., Kornilov, Matwey V., Korolev, Vladimir, Malanchev, Konstantin, Pruzhinskaya, Maria V., Sreejith, Sreevarsha
Publikováno v:
In: Baixeries, J., Ignatov, D.I., Kuznetsov, S.O., Stupnikov, S. (eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2023. Communications in Computer and Information Science, vol 2086. Springer, Cham
SNAD is an international project with a primary focus on detecting astronomical anomalies within large-scale surveys, using active learning and other machine learning algorithms. The work carried out by SNAD not only contributes to the discovery and
Externí odkaz:
http://arxiv.org/abs/2410.18875
Autor:
Pomar, Thierry Désiré, Steegemans, Tristan, Kumar, Sreejith, Bjørk, Rasmus, Lei, Zijin, Cheah, Erik, Schott, Rüdiger, Bøggild, Peter, Pryds, Nini, Wegscheider, Werner, Christensen, Dennis Valbjørn
Magnetometers based on the extraordinary magnetoresistance (EMR) effect are promising for applications which demand high sensitivity combined with room temperature operation but their application for magnetic field sensing requires further optimizati
Externí odkaz:
http://arxiv.org/abs/2410.17713
We consider the problem of shared randomness-assisted multiple access channel (MAC) simulation for product inputs and characterize the one-shot communication cost region via almost-matching inner and outer bounds in terms of the smooth max-informatio
Externí odkaz:
http://arxiv.org/abs/2410.17198
Autor:
Kornilov, M. V., Korolev, V. S., Malanchev, K. L., Lavrukhina, A. D., Russeil, E., Semenikhin, T. A., Gangler, E., Ishida, E. E. O., Pruzhinskaya, M. V., Volnova, A. A., Sreejith, S.
Publikováno v:
proceeding from Data Analytics and Management in Data Intensive Domains (DAMDID) 2024
We present coniferest, an open source generic purpose active anomaly detection framework written in Python. The package design and implemented algorithms are described. Currently, static outlier detection analysis is supported via the Isolation fores
Externí odkaz:
http://arxiv.org/abs/2410.17142
The trade-offs between error probabilities in quantum hypothesis testing are by now well-understood in the centralized setting, but much less is known for distributed settings. Here, we study a distributed binary hypothesis testing problem to infer a
Externí odkaz:
http://arxiv.org/abs/2410.08937