Miracle-dz/UniFAR-FTUs huggingface dataset:
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference

Machine learning (ML) has become increasingly important and performance-critical in modern data centers. This has led to interest inmodel serving systems, which performML inference and serve predictions to end-user applications. However, most existing model serving systems approach ML inference as an extension of conventional data serving workloads and miss critical opportunities for performance. In thispaper,wepresentWillump,a statistically-awareoptimizer forML inference that takes advantage of key properties ofML inference not shared by traditionalworkloads. First,ML models can often be approximated efficiently on many “easy” inputs by judiciously using a less expensive model for these inputs (e.g., not computing all the input features). Willump automatically generates such approximations from anML inference pipeline, providing up to 4.1× speedup without statistically significant accuracy loss. Second, MLmodels are often used in higher-level end-to-end queries in an ML application, such as computing the top K predictions for a recommendation model. Willump optimizes inference based on these higher-level queries by up to 5.7× over naïve batch inference. Willump combines these novel optimizations with standard compiler optimizations and a computation graph-aware feature caching scheme to automatically generate fast inference code for ML pipelines. We show that Willump improves performance of real-world ML inference pipelines by up to 23×, with its novel optimizations giving 3.6–5.7× speedups over compilation. We also show thatWillump integrates easily with existing model serving systems, such as Clipper.
Optimal jump set in hyperbolic conservation laws

We investigate qualitative properties of entropy solutions to hyperbolic conservation laws, and construct an entropy solution to a scalar conservation law for which the jump set is not closed, in particular, it is dense in a space-time domain. In a second part, we establish a similar result for hyperbolic systems. We give two different approaches for scalar conservation laws and hyperbolic systems in order to obtain these results. For the scalar case, the solutions are explicitly calculated.
PACO: Global Signal Restoration via PAtch COnsensus

Many signal processing algorithms break the target signal into overlapping segments (also called windows, or patches), process them separately, and then stitch them back into place to produce a unified output. At the overlaps, the final value of those samples that are estimated more than once needs to be decided in some way. Averaging, the simplest approach, tends to produce blurred results. Significant work has been devoted to this issue in recent years: several works explore the idea of a weighted average of the overlapped patches and/or pixels; a more recent approach is to promote agreement (consensus) between the patches at their intersections. This work investigates the case where consensus is imposed as a hard constraint on the restoration problem. This leads to a general framework applicable to all sorts of signals, problems, decomposition strategies, and featuring a number of theoretical and practical advantages over other similar methods. The framework itself consists of a general optimization problem and a simple and efficient \admm-based algorithm for solving it. We also show that the consensus step of the algorithm, which is the main bottleneck of similar methods, can be solved efficiently and easily for any arbitrary patch decomposition scheme. As an example of the potential of our framework, we propose a method for filling missing samples (inpainting) which can be applied to signals of any dimension, and show its effectiveness on audio, image and video signals.
Indications of non-conservative mass transfer in AMXPs

Context. Since the discovery of the first accreting millisecond X-ray pulsar (AMXP) SAX J1808.4−3658 in 1998, the family of these sources has kept growing. Currently, it has 22 members. All AMXPs are transients with usually very long quiescence periods, implying that the mass accretion rate in these systems is quite low and not constant. Moreover, for at least three sources, a non-conservative evolution was also proposed. Aims. Our purpose is to study the long term averaged mass-accretion rates in all the AMXPs discovered so far, to investigate a non-conservative mass-transfer scenario. Methods. We calculated the expected mass-transfer rate under the hypothesis of a conservative evolution based on their orbital periods and on the (minimum) mass of the secondary star (as derived from the mass function), driven by gravitational radiation and/or magnetic braking. Using this theoretical mass transfer, we determined the expected accretion luminosity of the systems. Thus, we achieved the lower limit to the distance of the sources by comparing the computed theoretical luminosity and the observed flux averaged over a time period of 20 years. Then, the lower limit to the distance of the sources was compared to the value of the distance reported in the literature to evaluate how reasonable the hypothesis of a conservative mass transfer is. Results. Based on a sample of 18 sources, we found strong evidence of a non-conservative mass transfer for five sources, for which the estimated distance lower limits are higher than their known distances. We also report hints of mass outflows in a further six sources. The discrepancy can be fixed under the hypothesis of a non-conservative mass transfer in which a fraction of the mass transferred onto the compact object is swept away from the system, likely due to the (rotating magnetic dipole) radiation pressure of the pulsar.
Rindler Observer Sublimation

In this note, we propose that an object moving with proper constant acceleration, i.e., a Rindler observer experiences a sublimation (or evaporation) process. In this first proposal, we do not consider the backreaction due to the sublimation. We focus on charged matter particles for the discussion, but for simplicity, we present the quantization of the neutrally charged massive scalar field in Rindler space. The amplitude from the Minkowski observer perspective of detection of matter particles that have been emitted by a Rindler observer, or accelerated detector, is computed in a new fashion. We make a comparison between the Rindler observer sublimation and the black hole evaporation. We present three variants of a new experimental setup, and we show that in two of them, the Minkowski amplitude of detection of matter particles corresponds to that of a thermal process. There is one, however, where deviations from thermality can be found. It is numerically explored.
Non-Wire Alternatives: An Additional Value Stream for Distributed Energy Resources

Distributed energy resources (DERs) can serve as non-wire alternatives (NWAs) to capacity expansion by managing peak load to avoid or delay traditional expansion projects. However, the value stream derived from using DERs as NWAs is usually not explicitly included in DER planning problems. In this paper, we study a planning problem that co-optimizes the investment and operation of DERs and the timing of capacity expansion. By including the timing of capacity expansion as a decision variable, we naturally incorporate the NWA-related value stream of DERs in the planning problem. Furthermore, we show that even though the resulting optimization problem could have millions of variables and is non-convex, an optimal solution can be found by solving a series of smaller linear problems. Finally, we present a NWAs planning problem using real data from the Seattle Campus of the University of Washington.
Anxiolytic drugs and altered hippocampal theta rhythms: The quantitative systems pharmacological approach

The spirit of systems pharmacology was adopted to study the possible mechanisms of anxiolytic drugs on hippocampal electric patterns. The frequency of the hippocampal theta rhythm increases linearly with the intensity of electrical stimulation to the brainstem. The reduction of mean theta frequency in this paradigm predicts the clinical efficacy of anxiolytic drugs. The purpose of this study was to investigate the mechanisms by which anxiolytics produce their characteristic effects on the slope and intercept of the stimulus-frequency relationship of hippocampal theta. A network of neuron populations that generates septo-hippocampal theta rhythm was modeled using a compartmental modeling technique. The influence of cellular and synaptic parameters on network frequency was studied. Results show that halving the rate of rise and fall of pyramidal hyperpolarization-activated (Ih) conductance lowers nPO elicited theta frequency at low levels of stimulation. Results also suggest that increasing the decay time constant of inhibitory post-synaptic current can reduce the frequency of low nPO stimulation elicited theta rhythm, while maximal synaptic conductance of GABA-mediated synapses has little effect on frequency. Given their similar effect on network dynamics as by known anxiolytics, these parameter manipulations may mimic or predict the biophysical manifestations of anxiolytic action within the septo-hippocampal system.
Slack Channels Ecology in Enterprises: How Employees Collaborate Through Group Chat

Despite the long history of studying instant messaging usage in organizations, we know very little about how today's people participate in group chat channels and interact with others. In this short note, we aim to update the existing knowledge on how group chat is used in the context of today's organizations. We have the privilege of collecting a total of 4300 publicly available group chat channels in Slack from an R\&D department in a multinational IT company. Through qualitative coding of 100 channels, we identified 9 channel categories such as project based channels and event channels. We further defined a feature metric with 21 features to depict the group communication style for these group chat channels, with which we successfully trained a machine learning model that can automatically classify a given group channel into one of the 9 categories. In addition, we illustrated how these communication metrics could be used for analyzing teams' collaboration activities. We focused on 117 project teams as we have their performance data, and further collected 54 out of the 117 teams' Slack group data and generated the communication style metrics for each of them. With these data, we are able to build a regression model to reveal the relationship between these group communication styles and one indicator of the project team performance.
Parallel epipolar stereo matching

Stereo matching is an important step in 3D reconstruction which is not yet solved satisfactorily. Efforts are necessary to enhance the matching quality and to reduce the processing time. To speed up the processing a parallel algorithm for coarse binocular epipolar image matching is presented. Data from epipolar image line pairs are fed into a special parallel processing structure which fulfills only simple operations such as convolution, averaging, and search for maxima. A priori information on possible maximum disparities is used too. A special smoothing algorithm can be applied to enhance the quality of the disparities. The method is to be applied as a first (coarse) approximation of 3D reconstruction using airborne digital stereo pushbroom cameras but it can also be used to fast evaluation of data from other stereo systems. The quality of the method is demonstrated with the often used Pentagon image pair.
Consensus of fractional-order multi-agent systems: Matrix inequality approach

This paper investigates the robust stabilisation of a class of fractional-order non-linear systems via fixed-order dynamic output feedback controller in terms of linear matrix inequalities (LMIs). The systematic stabilisation algorithm design for low-order controller based on direct Lyapunov approach is proposed. In the presented algorithm the conditions containing the bilinear variables are decoupled into separate conditions without imposing equality constraints or considering an iterative search of the controller parameters. There is no any limiting constraint on the state space matrices and also we assumed the most complete output feedback controller. Simulations results are given to approve the effectiveness and the straightforwardness of the proposed design.
Advanced analytical method based on Green's theorem for light transmission through subwavelength structures of multiple configurations in metal films

Nowadays, methods for analyzing light transmission through subwavelength structures are typically based on the mode expansion with Fourier series. However, these methods require sophisticated techniques and the solutions are in $k$-space, where the coupling physics that associates the boundary field in real space and the structure geometry becomes obscure. Moreover, the typical methods for the analysis of multi-layered hybrid configurations can be exhaustive due to the complex mode couplings at the interfaces of the layers. In contrast, an early method can analyze the single-slit transmission for solutions entirely in real space [F. L. Neerhoff and G. Mur, Appl. Sci. Res. 28, 73 (1973)] by rigorously formulating the field based on Green's theorem and obtaining two types of the Green's function for the cylindrical wave mode in free space and the symmetric waveguide modes inside the slit, respectively. In this article, we advance the method by developing a new type of Green's function for the asymmetric waveguide modes inside a groove. Since these wave modes are independent in real space, the coupling physics from the method becomes straightforward and the solutions are intuitive. With this meticulous method, we show that complex and multi-layered hybrid configurations can be easily analyzed with excellent accuracy. In addition, the method demonstrates the capability of translating the wave interaction problems to analytical physical models for further interpretation and study.
Locally Differentially Private Data Collection and Analysis

Local differential privacy (LDP) can provide each user with strong privacy guarantees under untrusted data curators while ensuring accurate statistics derived from privatized data. Due to its powerfulness, LDP has been widely adopted to protect privacy in various tasks (e.g., heavy hitters discovery, probability estimation) and systems (e.g., Google Chrome, Apple iOS). Although ${\epsilon}$-LDP has been proposed for many years, the more general notion of $({\epsilon}, {\delta})$-LDP has only been studied in very few papers, which mainly consider mean estimation for numeric data. Besides, prior solutions achieve $({\epsilon}, {\delta})$-LDP by leveraging Gaussian mechanism, which leads to low accuracy of the aggregated results. In this paper, we propose novel mechanisms that achieve $({\epsilon}, {\delta})$-LDP with high utility in data analytics and machine learning. Specifically, we first design $({\epsilon}, {\delta})$-LDP algorithms for collecting multi-dimensional numeric data, which can ensure higher accuracy than the optimal Gaussian mechanism while guaranteeing strong privacy for each user. Then, we investigate different local protocols for categorical attributes under $({\epsilon}, {\delta})$-LDP. Furthermore, we conduct theoretical analysis on the error bound and variance of the proposed algorithms. Experimental results on real and synthetic datasets demonstrate the high data utility of our proposed algorithms on both simple data statistics and complex machine learning models.
Measurement errors in the binary instrumental variable model

Instrumental variable methods can identify causal effects even when the treatment and outcome are confounded. We study the problem of imperfect measurements of the binary instrumental variable, treatment and outcome. We first consider nondifferential measurement errors, that is, the mismeasured variable does not depend on other variables given its true value. We show that the measurement error of the instrumental variable does not bias the estimate, that the measurement error of the treatment biases the estimate away from zero, and that the measurement error of the outcome biases the estimate toward zero. Moreover, we derive sharp bounds on the causal effects without additional assumptions. These bounds are informative because they exclude zero. We then consider differential measurement errors, and focus on sensitivity analyses in those settings.
Does quantum mechanics violate Bell's inequality?.

The EPR paradox is known as an interpretive problem, as well as a technical discovery in quantum mechanics. It defined the basic features of two-quantum entanglement, as needed to study the relationships between two non-commuting variables. In contrast, four variables are observed in a typical Bell experiment. This is no longer the same problem. The full complexity of this process can only be captured by the analysis of four-quantum entanglement. Indeed, a new paradox emerges in this context, with straightforward consequences. Quantum mechanics cannot violate CHSH-type inequalities, in the same sense in which local realism cannot do it. The solution is to assume that quantum correlations do not work at the level of full populations, when violations occur, but only apply to incompatible slices of input beams.
Architectural Middleware that Supports Building High-performance, Scalable, Ubiquitous, Intelligent Personal Assistants

Intelligent Personal Assistants (IPAs) are software agents that can perform tasks on behalf of individuals and assist them on many of their daily activities. IPAs capabilities are expanding rapidly due to the recent advances on areas such as natural language processing, machine learning, artificial cognition, and ubiquitous computing, which equip the agents with competences to understand what users say, collect information from everyday ubiquitous devices (e.g., smartphones, wearables, tablets, laptops, cars, household appliances, etc.), learn user preferences, deliver data-driven search results, and make decisions based on user's context. Apart from the inherent complexity of building such IPAs, developers and researchers have to address many critical architectural challenges (e.g., low-latency, scalability, concurrency, ubiquity, code mobility, interoperability, support to cognitive services and reasoning, to name a few.), thereby diverting them from their main goal: building IPAs. Thus, our contribution in this paper is twofold: 1) we propose an architecture for a platform-agnostic, high-performance, ubiquitous, and distributed middleware that alleviates the burdensome task of dealing with low-level implementation details when building IPAs by adding multiple abstraction layers that hide the underlying complexity; and 2) we present an implementation of the middleware that concretizes the aforementioned architecture and allows the development of high-level capabilities while scaling the system up to hundreds of thousands of IPAs with no extra effort. We demonstrate the powerfulness of our middleware by analyzing software metrics for complexity, effort, performance, cohesion and coupling when developing a conversational IPA.
On Low Complexity RLL Code for Visible Light Communication

Run length limited (RLL) codes are used in visible light communication (VLC) to avoid flicker and to support different dimming ranges such that communication is not affected by the variation in light intensity. In this paper, we propose a low complexity split phase code as RLL code in serial concatenation with the convolutional code as a forward error correcting code (FEC) for VLC. The split phase code can be represented by a two-state trellis-like code which can provide an iterative gain in FEC-RLL serial concatenation. We also use the extrinsic information transfer (EXIT) chart to explain the iterative decoding behavior of the proposed serial concatenated scheme. Furthermore, we use puncturing and compensation symbols to support various dimming range in VLC.
Detection of the self-regulation of star formation in galaxy discs

Stellar feedback has a notable influence on the formation and evolution of galaxies. However, direct observational evidence is scarce. We have performed stellar population analysis using MUSE optical spectra of the spiral galaxy NGC 628 and find that current maximum star formation in spatially resolved regions is regulated according to the level of star formation in the recent past. We propose a model based on the self-regulator or "bathtub" models, but for spatially resolved regions of the galaxy. We name it the "resolved self-regulator model" and show that the predictions of this model are in agreement with the presented observations. We observe star formation self-regulation and estimate the mass-loading factor, $\eta=2.5 \pm 0.5$, consistent with values predicted by galaxy formation models. The method described here will help provide better constraints on those models.
Imitation Learning for Non-Autoregressive Neural Machine Translation

Non-autoregressive translation models (NAT) have achieved impressive inference speedup. A potential issue of the existing NAT algorithms, however, is that the decoding is conducted in parallel, without directly considering previous context. In this paper, we propose an imitation learning framework for non-autoregressive machine translation, which still enjoys the fast translation speed but gives comparable translation performance compared to its auto-regressive counterpart. We conduct experiments on the IWSLT16, WMT14 and WMT16 datasets. Our proposed model achieves a significant speedup over the autoregressive models, while keeping the translation quality comparable to the autoregressive models. By sampling sentence length in parallel at inference time, we achieve the performance of 31.85 BLEU on WMT16 Ro\rightarrowEn and 30.68 BLEU on IWSLT16 En\rightarrowDe.
Finite-Time Stability of Switched Systems

In this paper, we study finite-time stability of switched systems. We present sufficient conditions in terms of multiple generalized Lyapunov functions for the origin of the switched system to be finite-time stable. We show that even if the value of the generalized Lyapunov function increases between consecutive switches, finite-time stability can still be guaranteed if the finite-time convergent mode is active long enough. We also present a method of designing a finite-time stabilizing switching law. As a case study, we use the developed schemes to design a finite-time stable state observer for linear switched systems for the case when only one of the modes is observable. Numerical examples demonstrate the efficacy of the proposed methods.