Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Convex Optimization with Stochastic Constraints: Zero Constraint Violation and Bandit Feedback

This paper studies online convex optimization with stochastic constraints. We propose a variant of the drift-plus-penalty algorithm that guarantees $O(\sqrt{T})$ expected regret and zero constraint violation, after a fixed number of iterations, which improves the vanilla drift-plus-penalty method with $O(\sqrt{T})$ constraint violation. Our algorithm is oblivious to the length of the time horizon $T$, in contrast to the vanilla drift-plus-penalty method. This is based on our novel drift lemma that provides time-varying bounds on the virtual queue drift and, as a result, leads to time-varying bounds on the expected virtual queue length. Moreover, we extend our framework to stochastic-constrained online convex optimization under two-point bandit feedback. We show that by adapting our algorithmic framework to the bandit feedback setting, we may still achieve $O(\sqrt{T})$ expected regret and zero constraint violation, improving upon the previous work for the case of identical constraint functions. Numerical results demonstrate our theoretical results.
RoFL: Robustness of Secure Federated Learning

Even though recent years have seen many attacks exposing severe vulnerabilities in Federated Learning (FL), a holistic understanding of what enables these attacks and how they can be mitigated effectively is still lacking. In this work, we demystify the inner workings of existing (targeted) attacks. We provide new insights into why these attacks are possible and why a definitive solution to FL robustness is challenging. We show that the need for ML algorithms to memorize tail data has significant implications for FL integrity. This phenomenon has largely been studied in the context of privacy; our analysis sheds light on its implications for ML integrity. We show that certain classes of severe attacks can be mitigated effectively by enforcing constraints such as norm bounds on clients’ updates. We investigate how to efficiently incorporate these constraints into secure FL protocols in the single-server setting. Based on this, we propose RoFL, a new secure FL system that extends secure aggregation with privacy-preserving input validation. Specifically, RoFL can enforce constraints such as L2 and L∞ bounds on high-dimensional encrypted model updates.
Improving the Transferability of Adversarial Attacks on Face Recognition With Beneficial Perturbation Feature Augmentation

Face recognition (FR) models can be easily fooled by adversarial examples, which are crafted by adding imperceptible perturbations on benign face images. The existence of adversarial face examples poses a great threat to the security of society. In order to build a more sustainable digital nation, in this paper, we improve the transferability of adversarial face examples to expose more blind spots of existing FR models. Though generating hard samples has shown its effectiveness in improving the generalization of models in training tasks, the effectiveness of utilizing this idea to improve the transferability of adversarial face examples remains unexplored. To this end, based on the property of hard samples and the symmetry between training tasks and adversarial attack tasks, we propose the concept of hard models, which have similar effects as hard samples for adversarial attack tasks. Utilizing the concept of hard models, we propose a novel attack method called Beneficial Perturbation Feature Augmentation Attack (BPFA), which reduces the overfitting of adversarial examples to surrogate FR models by constantly generating new hard models to craft the adversarial examples. Specifically, in the backpropagation, BPFA records the gradients on pre-selected feature maps and uses the gradient on the input image to craft the adversarial example. In the next forward propagation, BPFA leverages the recorded gradients to add beneficial perturbations on their corresponding feature maps to increase the loss. Extensive experiments demonstrate that BPFA can significantly boost the transferability of adversarial attacks on FR.
f-Divergences and Their Applications in Lossy Compression and Bounding Generalization Error

In this paper, we provide three applications for <inline-formula> <tex-math notation="LaTeX">$ {\mathsf {f}}$ </tex-math></inline-formula>-divergences: (i) we introduce Sanov’s upper bound on the tail probability of the sum of independent random variables based on super-modular <inline-formula> <tex-math notation="LaTeX">$ {\mathsf {f}}$ </tex-math></inline-formula>-divergence and show that our generalized Sanov’s bound strictly improves over ordinary one, (ii) we consider the lossy compression problem which studies the set of achievable rates for a given distortion and code length. We extend the rate-distortion function using mutual <inline-formula> <tex-math notation="LaTeX">$ {\mathsf {f}}$ </tex-math></inline-formula>-information and provide new and strictly better bounds on achievable rates in the finite blocklength regime using super-modular <inline-formula> <tex-math notation="LaTeX">$ {\mathsf {f}}$ </tex-math></inline-formula>-divergences, and (iii) we provide a connection between the generalization error of algorithms with bounded input/output mutual <inline-formula> <tex-math notation="LaTeX">$ {\mathsf {f}}$ </tex-math></inline-formula>-information and a generalized rate-distortion problem. This connection allows us to bound the generalization error of learning algorithms using lower bounds on the <inline-formula> <tex-math notation="LaTeX">$ {\mathsf {f}}$ </tex-math></inline-formula>-rate -distortion function. Our bound is based on a new lower bound on the rate-distortion function that (for some examples) strictly improves over previously best-known bounds.
Anderson localization and swing mobility edge in curved spacetime

We construct a quasiperiodic lattice model in curved spacetime to explore the crossover concerning both condensed matter and curved spacetime physics. We study the related Anderson localization and find that the model has a clear boundary of localized-extended phase separation, which leads to a swing mobility edge, i.e., the coexistence of localized, swing and sub-extended phases. The swing mobility edge, first reported here, features the phase-dependent eigenstate, that is, the eigenstate swing between the extended and localized state for differnt phase parameter of the quasiperiodic potential. Furthermore, A novel self-consistent segmentation method is developed to calculate the analytical expression of the critical point of phase separation, and the rich phase diagram is obtained by calculating the fractal dimension and scaling index in multifractal analysis.
Evidence of spin-pumping effect in the ferromagnetic resonance of coupled trilayers

The spin dynamics between two ultrathin ferromagnetic layers exchange coupled via a nonmagnetic spacer is studied using in situ ferromagnetic resonance. The angular and the temperature dependence of the linewidth, especially the pronounced changes of the former, can be understood assuming the presence of an additional Gilbert damping resulting from the spin-current pumped through the interface between the ferromagnetic and nonmagnetic material or by considering the dynamic part of the interlayer exchange coupling. The competition between the Gilbert damping inherent in the ferromagnetic film and the Gilbert damping developed by the interface leads to an irregular behavior of the temperature dependence of the resonance linewidth for both the in-phase and out-of-phase processing modes. It is shown that the oscillatory nature of the coupling is also revealed in the dependence of the resonance linewidth ΔH on the spacer thickness.
A fuzzy-stochastic robust programming model for regional air quality management under uncertainty

This paper proposes a hybrid fuzzy-stochastic robust programming (FSRP) method and applies it to a case study of regional air quality management. As an extension of the existing fuzzy-robust programming and chance-constrained programming methods, FSRP can explicitly address complexities and uncertainties without unrealistic simplifications. Parameters in the FSRP model can be expressed as PDFs and/or membership functions, such that robustness of the optimization process can be enhanced. In its solution process, the FSRP model is converted to a deterministic version through transforming m imprecise constraints into 2 km precise inclusive constraints that correspond to k f -cut levels (under each given significance level). Results of the case study indicate that FSRP is applicable to problems that involve a variety of uncertainties. Air pollution control invariably involves a number of processes with socio-economic and environmental implications. These processes are associated with extensive uncertainties due to their complex, interactive, dynamic, and multiobjective features. Through the FSRP modeling study, useful solutions for planning regional air quality management practices have been generated. They reflect complex trade-offs between environmental and economic considerations. Willingness to pay higher operating costs will guarantee meeting environmental objectives; however, a desire to reduce the costs will run the risk of potentially violating the emission and/or ambient-air-quality standards.
The effect of non-linearities on statistical distributions in the theory of sea waves

The statistical density function is derived for a variable (such as the surface elevation in a random sea) that is ‘weakly non-linear’. In the first approximation the distribution is Gaussian, as is well known. In higher approximations it is shown that the distribution is given by successive sums of a Gram–Charlier series; not quite in the form that has sometimes been used as an empirical fit for observed distributions, but in a modified form due to Edgeworth. It is shown that the cumulants of the distribution are much simpler to calculate than the corresponding moments; and the approximate distributions are in fact derived by inversion of the cumulant-generating function. The theory is applied to random surface waves on water. The third cumulant and hence the skewness of the distribution of surface elevation is evaluated explicity in terms of the directional energy spectrum. It is shown that the skewness λ3 is generally positive, and positive upper and lower bounds for λ3 are derived. The theoretical results are compared with some measurements made by Kinsman (1960). It is found that for free, undamped surface waves the skewness of the distribution of surface slopes is of a higher order than the skewness of the surface elevation. Hence the observed skewness of the slopes may be a sensitive indicator of energy transfer and dissipation within the water.
Least-Squares Finite-Element Method of Multidimensional Radiative Heat Transfer in Absorbing and Scattering Media

A least-squares finite-element method (LSFEM) is developed to simulate the radiative transfer in absorbing and scattering media. This model is based on the discrete ordinates method (DOM) and the least-squares finite-element method. It can be presented as an alternative to the traditional Galerkin finite-element method (GFEM). This method is used to overcome the spurious oscillation which be found in the GFEM for radiative transfer. In addition, the resulting coefficients matrix produced by the LSFEM is symmetric and positive-definite. Only half of a sparse matrix needs to be stored. Some efficient iterative algorithms for symmetrical systems of equations can be used successfully. In order to validate this method, two 2-D problems and a 3-D problem of radiative transfer are examined. The computational results indicate that the present model can simulate the radiative transfer in the multidimensional complex geometric enclosure efficiently and accurately. More important, the present model is proved to be wiggle-free.
Excat Nonparametric Tests of Orthogonality and Random Walk in the Presence of a Drift Parameter

In this paper, finite-sample nonparametric tests of conditional independence and random walk are extended to allow for an unknown drift parameter. The tests proposed are based on simultaneous inference methods and remain exact in the presence of general forms of feedback, nonnormality and heterskedasticity. Further, in two simulation studies, the authors confirm that the nonparametric procedures are reliable and find that they display power comparable or superior to that of conventional tests. Copyright 1997 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association. (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.)
Lidar Descriptions of Mixing-Layer Thickness Characteristics in a Complex Terrain/Coastal Environment.

Abstract Airborne lidar and supplementary measurements made during a major study of air chemistry in southern California (SCCCAMP 1985) provided a rare opportunity to examine atmospheric boundary-layer structure in a coastal area with complex terrain. This structure results from a combination of daytime heating or convection in the boundary layer (CBL), the intrusion of a marine layer into the inland areas, the thermal internal boundary layer (TIBL) formed within the marine onshore flow, inland growth of the TIBL, interactions of the CBL and the TIBL, and airflow interactions with terrain features. Measurements showed offshore mixing-layer thicknesses during SCCCAMP to be quite uniform spatially and day to day at 100–200 m. Movement of this layer onshore occurred readily with terrain that sloped gradually upward (e.g., to 300 m MSL at 50 km inland), but was effectively blocked by a 400–500 m high coastal ridge. In the higher terrain beyond the coastal ridge, aerosol layers aloft were often created as a re.
Structure and linearization in disharmonic word orders

So-called “harmonic” word orders, which reflect either consistent head-initial or head-final order (cf. Hawkins 1983), have received much attention in both the generative and the typological literature. Thus, for example, it is now well-known that some of Greenberg’s “word order universals” represent robust generalisations which hold across the majority of languages surveyed to date (cf. Dryer 1992, Haspelmath et al. 2005). The generative account of these recurring patterns is also well-established: assuming (1a), the tendency for V(erb)-O(bject), Aux(iliary)-V(erb), C(omplementizer)-Sentence and prepositions to co-occur, while the opposite is true for OV languages, can, for example, be ascribed to different settings of the Head Parameter (1b):
Encoding of environmental illumination by primate melanopsin neurons

Light regulates physiology, mood, and behavior through signals sent to the brain by intrinsically photosensitive retinal ganglion cells (ipRGCs). How primate ipRGCs sense light is unclear, as they are rare and challenging to target for electrophysiological recording. We developed a method of acute identification within the live, ex vivo retina. Using it, we found that ipRGCs of the macaque monkey are highly specialized to encode irradiance (the overall intensity of illumination) by blurring spatial, temporal, and chromatic features of the visual scene. We describe mechanisms at the molecular, cellular, and population scales that support irradiance encoding across orders-of-magnitude changes in light intensity. These mechanisms are conserved quantitatively across the ~70 million years of evolution that separate macaques from mice. Description Encoding illumination in primates Light is an important environmental factor for most organisms because it regulates many physiological functions and behaviors. Central to this regulation is a photoreceptive molecule called melanopsin and its actions within the intrinsically photosensitive retinal ganglion cells (ipRGCs), neurons that send signals from the retina to the brain. Little is known about the ipRGCs of primates. Liu et al. developed a method of identifying primate ipRGCs and used it to investigate how they sense the visual world (see the Perspective by Martin). They found that ipRGCs encode the overall intensity of environmental illumination using specializations that are distributed across scales of biological organization. These cells thus show insensitivity to image detail and a wide dynamic range. —PRS A rare type of primate retinal neuron encodes irradiance by blurring across space, time, and wavelength.
The effect of antithrombotic treatment on the fecal immunochemical test for colorectal cancer screening: a nationwide cross-sectional study

BACKGROUND : Screening for colorectal cancer (CRC) using the fecal immunochemical test (FIT) has been widely adopted. The use of antithrombotic treatment is increasing in the Western world. This study aimed to assess the effects of antithrombotic treatment on the FIT-based Danish national screening program for CRC. METHODS : This was a cross-sectional study of all individuals returning a FIT from 2014 until 2016. The effect of antithrombotic treatment on FIT positivity and the positive predictive value (PPV) were assessed using proportions and multivariable Poisson regression. RESULTS : Of 884 036 invited individuals, we identified 551 570 participants. A positive FIT was observed in 9052 of 77 007 individuals (11.8 %) receiving antithrombotic treatment compared with 28 387 of 474 587 individuals (6.0 %) receiving no treatment. The adjusted relative risk (RR) for a positive FIT was 1.59 (95 %CI 1.56-1.63) for any treatment. Nonvitamin K oral anticoagulants (NOACs) were associated with the largest increase in FIT positivity (adjusted RR 2.40, 95 %CI 2.48-2.54). The proportion of CRC detected at colonoscopy was slightly lower among patients on antithrombotic treatment (6.0 %, 95 %CI 5.5 %-6.6 %) than among treatment-naïve patients (6.4 %, 95 %CI 6.1 %-6.7 %). The PPV for CRC or high risk adenomas was decreased nearly twofold in patients treated with NOAC (adjusted RR 0.58, 95 %CI 0.51-0.66]). CONCLUSION : Antithrombotic treatment was associated with a decreased PPV in FIT-based CRC screening.
Aerial Observations of the Yugoslavian Bora

Abstract The first aircraft observations of the bora in Yugoslavia were accomplished during the ALPEX project in 1982. Data from all five ALPEX bora flights have been analyzed in a comparative study of bora structure. Although the bora varies considerably in depth, in the strength of the incoming low level flow, and in the direction of the winds aloft, several common features are evident. These include: upstream descent and acceleration beginning where the mountains rise; an approximate coincidence between the depth of the uppermost descending streamline and the wind reversal level upstream (when a reversal exists); a decoupling of the flow aloft associated with a splitting of the inversion and the formation of a thick mixed layer downstream; a narrow region of intense turbulence and an ascending jet just downstream of the plunging bora. The bora structure is similar in many respects to the Boulder windstorm. Internal hydraulic theory, taking into account the decoupling effect of the intermediate layer, a.
Massive star formation in galaxies: radiative transfer models of the UV to millimetre emission of starburst galaxies

We present illustrative models for the UV to millimeter emission of starburst galaxies which are treated as an ensemble of optically thick giant molecular clouds (GMCs) centrally illuminated by recently formed stars. The models follow the evolution of the GMCs due to the ionization-induced expansion of the HII regions and the evolution of the stellar population within the GMC according to the Bruzual & Charlot stellar population synthesis models. The effect of transiently heated dust grains/PAHs to the radiative transfer, as well as multiple scattering, is taken into account. The expansion of the HII regions and the formation of a narrow neutral shell naturally explains why the emission from PAHs dominates over that from hot dust in the near to mid-IR, an emerging characteristic of the infrared spectra of starburst galaxies. The models allow us to relate the observed properties of a galaxy to its age and star formation history. We find that exponentially decaying 10^7-10^8 yrs old bursts can explain the IRAS colours of starburst galaxies. The models are also shown to account satisfactorily for the multiwavelength data on the prototypical starburst galaxy M82 and NGC6090, a starburst galaxy recently observed by ISO. In M82 we find evidence for two bursts separated by 10^7yrs. In NGC6090 we find that at least part of the far-IR excess may be due to the age of the burst (6.4 x 10^7yrs). We also make predictions about the evolution of the luminosity of starbursts at different wavelengths which indicate that far-IR surveys may preferentially detect older starbursts than mid-IR surveys.
A multipopulation genetic algorithm to solve the inverse problem in hydrogeology

The inverse problem of groundwater flow is treated with an automatic method that can produce several alternative solutions at once. During their joint optimization, these solutions can exchange information in order to maintain some diversity and thus avoid a systematic premature convergence toward a single local minimum. Although genetic algorithms are capable of doing this, they have not often been used in groundwater inverse optimization. First, a specific multipopulation genetic algorithm is developed. It is then tested on two synthetic cases of steady state flow with transmissivity values extending over 4 orders of magnitude. The first test is nonparametric and optimizes as many parameters as those used to define the reference case. The second test uses a sort of “pilot point” parametrization. The optimization is carried out on a limited number of perturbations that are interpolated and superimposed on an initial transmissivity field. In view of the good quality of the results, these initial attempts provide incentives to further develop genetic algorithms in groundwater inverse problems.