New Publications and Lectures
- Journal Paper submitted to Mathematical Statistics and Learning: E Riegler, G. Koliander, D. Stotz, and H. Bölcskei, Completion of Matrices with Low Description Complexit, arXiv:2303.03731 [cs.IT].
- Journal Paper accepted at Information and Inference: A Journal of the IMA: E Riegler, G. Koliander, and H. Bölcskei, Lossy Compression of General Random Variabls, arXiv:2111.12312 [math.PR].
- Plenary tutorial at the 2022 IEEE European School of Information Theory.
- Journal Paper submitted to Information and Inference: A Journal of the IMA: E Riegler, G. Koliander, and H. Bölcskei, “Lossy Compression of General Random Variables,” arXiv:2111.12312 [math.PR].
- New Lecture on Learning, Classification, and Compression at the Swiss Federal Institute of Technology Zurich, Switzerland, Feb. 2021–Jun. 2021.
- Journal Paper in IEEE Trans. Inf. Theory: G. Alberti, H. Bölcskei, C. De Lellis, G. Koliander, and E. Riegler, “Lossless Analog Compression,” IEEE Trans. Inf. Theory, vol. 65, no. 11, pp. 7480–7513, Nov. 2019, arXiv:1803.06887 [math.FA].
- Book Chapter in Information-theoretic Methods in Data Science: E. Riegler and H. Bölcskei, “Uncertainty relations and sparse signal recovery,” in Information-theoretic Methods in Data Science, M. Rodrigues and Y. Eldar, Eds., Cambridge University Press, arXiv:1811.03996 [cs.IT].