There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

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Convex Analysisの二,三の進展について

On robust estimation of the location parameter

Nociceptor inputs can trigger a prolonged but reversible increase in the excitability and synaptic efficacy of neurons in central nociceptive pathways, the phenomenon of central sensitization. Central sensitization manifests as pain hypersensitivity, particularly dynamic tactile allodynia, secondary punctate or pressure hyperalgesia, aftersensations, and enhanced temporal summation. It can be readily and rapidly elicited in human volunteers by diverse experimental noxious conditioning stimuli to skin, muscles or viscera, and in addition to producing pain hypersensitivity, results in secondary changes in brain activity that can be detected by electrophysiological or imaging techniques. Studies in clinical cohorts reveal changes in pain sensitivity that have been interpreted as revealing an important contribution of central sensitization to the pain phenotype in patients with fibromyalgia, osteoarthritis, musculoskeletal disorders with generalized pain hypersensitivity, headache, temporomandibular joint disorders, dental pain, neuropathic pain, visceral pain hypersensitivity disorders and post-surgical pain. The comorbidity of those pain hypersensitivity syndromes that present in the absence of inflammation or a neural lesion, their similar pattern of clinical presentation and response to centrally acting analgesics, may reflect a commonality of central sensitization to their pathophysiology. An important question that still needs to be determined is whether there are individuals with a higher inherited propensity for developing central sensitization than others, and if so, whether this conveys an increased risk in both developing conditions with pain hypersensitivity, and their chronification. Diagnostic criteria to establish the presence of central sensitization in patients will greatly assist the phenotyping of patients for choosing treatments that produce analgesia by normalizing hyperexcitable central neural activity. We have certainly come a long way since the first discovery of activity-dependent synaptic plasticity in the spinal cord and the revelation that it occurs and produces pain hypersensitivity in patients. Nevertheless, discovering the genetic and environmental contributors to and objective biomarkers of central sensitization will be highly beneficial, as will additional treatment options to prevent or reduce this prevalent and promiscuous form of pain plasticity.

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Central sensitization: implications for the diagnosis and treatment of pain.

Fibromyalgia - are there different mechanisms in the processing of pain? A double blind, cross-over comparison of intravenous ketamine, morphine, lidocaine and placebol

Fibromyalgia - are there different mechanisms in the processing of pain? A double blind, cross-over comparison of intravenous ketamine, morphine, lidocaine and placebol.

This paper considers the precoder designs for successive zero-forcing dirty paper coding (SZF-DPC), a suboptimal transmission technique for MIMO broadcast channels (MIMO BCs). Existing precoder designs for SZF-DPC often consider a sum power constraint. In this paper, we address the precoder design for SZF-DPC with per-antenna power constraints (PAPCs), which has not been well studied. First, we formulate the precoder design as a rank-constrained optimization problem, which is generally difficult to handle. To solve this problem, we follow a relaxation approach, and prove that the optimal solution of the relaxed problem is also optimal for the original problem. Considering the relaxed problem, we propose a numerically efficient algorithm to find the optimal solution, which exhibits a fast convergence rate. Suboptimal precoder designs, with lower computational complexity, are also presented, and compared with the optimal ones in terms of achievable sum rate and computational complexity.

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Successive zero-forcing DPC with per-antenna power constraint: Optimal and suboptimal designs

This work addresses the problem of joint downlink beamforming and power control with general quality of service (QoS) constraints. Previous work on downlink beamforming does not provide a framework to handle the additional constraints in a straightforward fashion. Herein, it is shown that the QoS requirements can be formulated as quadratic constraints to a convex optimization problem. An efficient algorithm for solving the problem, based on semidefinite optimization is presented. To demonstrate the performance of the proposed approach, we present an example using quadratic constraints to greatly decrease the probability of a low instantaneous signal to interference and noise ratio (SINR) for a receiver equipped with a RAKE combiner.

Optimal downlink beamforming with additional constraints

Link adaptation provides high spectral efficiency in wireless communications by selecting appropriate transmission parameters, e.g., the modulation and coding scheme (MCS), based on the instantaneous wireless channel. However, link adaptation suffers from impairments due to channel state information (CSI) feedback delay. In this paper, we extend the data-driven MCS selection scheme in our previous work to the case of outdated CSI, by assuming that CSI history is available to the system. We present two approaches that leverage the CSI history to optimally select the MCS for the current channel, i.e., i) an end-to-end (E2E) machine learning approach and ii) a hybrid data-driven and model-based approach. The E2E method uses the CSI history as input to a neural network for MCS selection. Conversely, the hybrid method uses a lower-dimensionality sufficient statistic for the instantaneous CSI, computed from the CSI history, as input to a neural network for MCS selection. We demonstrate that replacing the CSI history with the sufficient statistic comes without loss of generality. Moreover, by means of numerical experiments, we show that both approaches effectively compensate for the feedback delay. However, we advocate the hybrid approach as it comes with the additional benefits of i) a smaller neural network, which in turn requires a lower amount of data and training time, ii) improved explainability, and iii) better insights into optimization choices.

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Wireless link adaptation with outdated CSI — a hybrid data-driven and model-based approach

In this work we shed light on the problem of precoding and user selection in MIMO networks. We formulate the problem using the framework of stable matching, whereby a set of users wish to be matched to a set of serving base stations, such as to maximize the sum-rate performance of the system. Though the problem is NP-hard, we propose a suboptimal heuristic that tackles the problem in a distributed fashion: we apply a many-to-one stable matching algorithm to generate a sequence of matchings, and the Weighted MMSE algorithm to perform the precoding. We benchmark our algorithm againt the recently proposed Weighted MMSE with User Assignment algorithm [1].

Mats Bengtsson

Papers

Fibromyalgia - are there different mechanisms in the processing of pain? A double blind, cross-over comparison of intravenous ketamine, morphine, lidocaine and placebol.

Successive zero-forcing DPC with per-antenna power constraint: Optimal and suboptimal designs

Optimal downlink beamforming with additional constraints

Wireless link adaptation with outdated CSI — a hybrid data-driven and model-based approach

Distributed precoding and user selection in MIMO interfering networks