Tziavelis, N., Giannakopoulos, I., Doka, K., Koziris, N.
& Karras, P. (2019).
Equitable Stable Matchings in Quadratic Time. I H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox & R. Garnett (red.),
Advances in Neural Information Processing Systems 32 (NIPS 2019): Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019 (Bind 32, s. 455-465). Curran Associates, Inc..
https://papers.nips.cc/paper/8337-equitable-stable-matchings-in-quadratic-time
Tzavelis, N., Giannakopoulos, I., Johansen, R. Q., Doka, K., Koziris, N.
& Karras, P. (2020).
Fair Procedures for Fair Stable Marriage Outcomes. I
AAAI 2020 - 34th AAAI Conference on Artificial Intelligence (Bind 34, no. 5, s. 7269-7276). AAAI Press.
https://doi.org/10.1609/aaai.v34i05.6218
Tunç, H. C., Abdulla, P. A., Chakraborty, S., Krishna, S., Mathur, U.
& Pavlogiannis, A. (2023).
Optimal Reads-From Consistency Checking for C11-Style Memory Models.
Proceedings of the ACM on Programming Languages ,
7(PLDI), 761–785. Artikel 137.
https://doi.org/10.1145/3591251
Tsourakakis, C. E., Mitzenmacher, M.
, Larsen, K. G., Blasiok, J., Lawson, B., Nakkiran, P. & Nakos, V. (2018).
Predicting Positive and Negative Links with Noisy Queries: Theory Practice. arxiv.org.
http://arxiv.org/abs/1709.07308
Tsitsulin, A.
, Mottin, D., Karras, P., Bronstein, A. & Müller, E. (2019).
Spectral graph complexity. I L. Liu & R. White (red.),
The Web Conference 2019 - Companion of the World Wide Web Conference, WWW 2019 (s. 308-309). Association for Computing Machinery.
https://doi.org/10.1145/3308560.3316589
Tsitsulin, A., Munkhoeva, M.
, Mottin, D., Karras, P., Bronstein, A., Oseledets, I. & Müller, E. (2020).
The Shape of Data: Intrinsic Distance for Data Distributions. Afhandling præsenteret på The International Conference on Learning Representations (ICLR), Ababa, Etiopien.
Tsitsulin, A., Munkhoeva, M.
, Mottin, D., Karras, P., Oseledets, I. & Mueller, E. (2021).
FREDE: Anytime Graph Embeddings.
Proceedings of the VLDB Endowment,
14(6), 1102-1110.
https://doi.org/10.14778/3447689.3447713
Tsirogiannis, C., Sandel, B. S. & Kalvisa, A. (2014).
New Algorithms for Computing Phylogenetic Biodiversity. I D. Brown & B. Morgenstern (red.),
Algorithms in Bioinformatics: 14th International Workshop, WABI 2014, Wroclaw, Poland, September 8-10, 2014. Proceedings (s. 187-203). Springer VS.
https://doi.org/10.1007/978-3-662-44753-6_15
Truica, C.-O., Apostol, E. S., Stefu, T.
& Karras, P. (2021).
A Deep Learning Architecture for Audience Interest Prediction of News Topic on Social Media. I Y. Velegrakis, D. Zeinalipour-Yazti, P. K. Chrysanthis & F. Guerra (red.),
Advances in Database Technology - EDBT 2021: 24th International Conference on Extending Database Technology, Proceedings (s. 588-599). openproceedings.org.
https://doi.org/10.5441/002/edbt.2021.69
Trittenbach, H., Böhm, K.
& Assent, I. (2020).
Active Learning of SVDD Hyperparameter Values. I G. Webb, Z. Zhang, V. S. Tseng, G. Williams, M. Vlachos & L. Cao (red.),
Proceedings - 2020 IEEE 7th International Conference on Data Science and Advanced Analytics, DSAA 2020 (s. 109-117). Artikel 9260103 IEEE.
https://doi.org/10.1109/DSAA49011.2020.00023
Trifiletti, R.
, Nielsen, J. B., Frederiksen, T. K. & Jakobsen, T. P. (2016).
On the Complexity of Additively Homomorphic UC Commitments. I E. Kushilevitz & T. Malkin (red.),
Theory of Cryptography - 13th International Conference, TCC 2016-A, Proceedings (Bind 9562, s. 542-565). Springer VS.
https://doi.org/10.1007/978-3-662-49096-9