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This paper studies optimization of zero-delay source-channel codes, and specifically the problem of obtaining globally optimal transformations that map between the source space and the channel space, under a given transmission power…

Information Theory · Computer Science 2013-04-26 Mustafa S. Mehmetoglu , Emrah Akyol , Kenneth Rose

In this paper, we address the problem of learning a binary (positive vs. negative) classifier given Positive and Unlabeled data commonly referred to as PU learning. Although rudimentary techniques like clustering, out-of-distribution…

Machine Learning · Computer Science 2023-10-09 Omar Zamzam , Haleh Akrami , Mahdi Soltanolkotabi , Richard Leahy

We consider the zeroth-order optimization problem in the huge-scale setting, where the dimension of the problem is so large that performing even basic vector operations on the decision variables is infeasible. In this paper, we propose a…

Optimization and Control · Mathematics 2021-08-17 HanQin Cai , Yuchen Lou , Daniel McKenzie , Wotao Yin

Binary optimization, a representative subclass of discrete optimization, plays an important role in mathematical optimization and has various applications in computer vision and machine learning. Usually, binary optimization problems are…

Optimization and Control · Mathematics 2021-05-18 Huan Xiong , Mengyang Yu , Li Liu , Fan Zhu , Fumin Shen , Ling Shao

The problem of modulation classification for a multiple-antenna (MIMO) system employing orthogonal frequency division multiplexing (OFDM) is investigated under the assumption of unknown frequency-selective fading channels and…

Information Theory · Computer Science 2016-04-11 Yu Liu , Osvaldo Simeone , Alexander M. Haimovich , Wei Su

This paper presents a novel framework, namely Deep Cross-modality Spectral Hashing (DCSH), to tackle the unsupervised learning problem of binary hash codes for efficient cross-modal retrieval. The framework is a two-step hashing approach…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Tuan Hoang , Thanh-Toan Do , Tam V. Nguyen , Ngai-Man Cheung

Massive multiple input and multiple output (MIMO) systems with orthogonal frequency division multiplexing (OFDM) are foundational for downlink multi-user (MU) communication in future wireless networks, for their ability to enhance spectral…

Signal Processing · Electrical Eng. & Systems 2025-07-30 Erdeng Zhang , Shuntian Zheng , Sheng Wu , Haoge Jia , Zhe Ji , Ailing Xiao

We present a new family of signal constellations, called log constellations, that can be used to design near-capacity coded modulation schemes over additive exponential noise (AEN) channels. Log constellations are designed by geometrically…

Information Theory · Computer Science 2011-11-29 Stéphane Y. Le Goff

In this paper, we derive a maximum likelihood (ML) decoder of the differential data in a decode-and-forward (DF) based cooperative communication system utilizing uncoded transmissions. This decoder is applicable to complex-valued unitary…

Information Theory · Computer Science 2012-04-12 Manav R. Bhatnagar

Polar coding over a class of binary discrete memoryless channels with channel knowledge at the encoder is studied. It is shown that polar codes achieve the capacity of convex and one-sided classes of symmetric channels.

Information Theory · Computer Science 2013-12-02 Mine Alsan

We address the problem of image translation between domains or modalities for which no direct paired data is available (i.e. zero-pair translation). We propose mix and match networks, based on multiple encoders and decoders aligned in such…

Computer Vision and Pattern Recognition · Computer Science 2018-04-09 Yaxing Wang , Joost van de Weijer , Luis Herranz

We consider the joint constellation design problem for the noncoherent multiple-input multiple-output multiple-access channel (MAC). By analyzing the noncoherent maximum-likelihood detection error, we propose novel design criteria so as to…

Information Theory · Computer Science 2022-07-06 Khac-Hoang Ngo , Sheng Yang , Maxime Guillaud , Alexis Decurninge

We propose an autoencoder-based geometric shaping that learns a constellation robust to SNR and laser linewidth estimation errors. This constellation maintains shaping gain in mutual information (up to 0.3 bits/symbol) with respect to QAM…

Signal Processing · Electrical Eng. & Systems 2022-04-26 Ognjen Jovanovic , Metodi P. Yankov , Francesco Da Ros , Darko Zibar

This paper considers a discrete-time multiuser multiple-input single-output (MISO) Gaussian broadcast channel~(BC), in which channel state information (CSI) is available at both the transmitter and the receivers. The flexible and explicit…

Information Theory · Computer Science 2016-12-21 Zheng Dong , Yan-Yu Zhang , Jian-Kang Zhang , Xiang-Chuan Gao

An asymptotically optimal trellis-coded modulation (TCM) encoder requires the joint design of the encoder and the binary labeling of the constellation. Since analytical approaches are unknown, the only available solution is to perform an…

Information Theory · Computer Science 2015-01-07 Alex Alvarado , Alexandre Graell i Amat , Fredrik Brannstrom , Erik Agrell

Bidirectional mapping-based generalized zero-shot learning (GZSL) methods rely on the quality of synthesized features to recognize seen and unseen data. Therefore, learning a joint distribution of seen-unseen domains and preserving domain…

Computer Vision and Pattern Recognition · Computer Science 2021-02-22 Tasfia Shermin , Shyh Wei Teng , Ferdous Sohel , Manzur Murshed , Guojun Lu

The problem of blind channel estimation for SISO-OFDM systems using second-order statistics (SOS) is addressed. A comparison of two prominent SOS-based techniques: subspace-decomposition and precoding-induced correlation-averaging…

Signal Processing · Electrical Eng. & Systems 2025-08-12 Sameera Bharadwaja H. , D. K. Mehra

One of the hallmarks of human intelligence is the ability to compose learned knowledge into novel concepts which can be recognized without a single training example. In contrast, current state-of-the-art methods require hundreds of training…

Computer Vision and Pattern Recognition · Computer Science 2019-05-16 Senthil Purushwalkam , Maximilian Nickel , Abhinav Gupta , Marc'Aurelio Ranzato

Channel polarization is a method of constructing capacity achieving codes for symmetric binary-input discrete memoryless channels (B-DMCs) [1]. In the original paper, the construction complexity is exponential in the blocklength. In this…

Information Theory · Computer Science 2009-05-23 Ryuhei Mori , Toshiyuki Tanaka

A practical $2^m$-ary polar coded modulation (PCM) scheme with optimal constellation labeling is proposed. To efficiently find the optimal labeling rule, the search space is reduced by exploiting the symmetry properties of the channels.…

Information Theory · Computer Science 2013-07-11 Kai Chen , Kai Niu , Jiaru Lin
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