Understanding the Impact of Adversarial Robustness on Accuracy Disparity

While it has long been empirically observed that adversarial robustness may be at odds with standard accuracy and may have further disparate impacts on different classes, it remains an open question to what extent such observations hold and how the class imbalance plays a role within. In this paper, we attempt to understand this question of accuracy disparity by taking a closer look at linear classifiers under a Gaussian mixture model. We decompose the impact of adversarial robustness into two parts: an inherent effect that will degrade the standard accuracy on all classes due to the robustness constraint, and the other caused by the class imbalance ratio, which will increase the accuracy disparity compared to standard training. Furthermore, we also show that such effects extend beyond the Gaussian mixture model, by generalizing our data model to the general family of stable distributions. More specifically, we demonstrate that while the constraint of adversarial robustness consistently degrades the standard accuracy in the balanced class setting, the class imbalance ratio plays a fundamentally different role in accuracy disparity compared to the Gaussian case, due to the heavy tail of the stable distribution. We additionally perform experiments on both synthetic and real-world datasets to corroborate our theoretical findings. Our empirical results also suggest that the implications may extend to nonlinear models over real-world datasets. Our code is publicly available on GitHub at https://github.com/Accuracy-Disparity/AT-on-AD.Comment: Accepted at ICML 202

Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective

Linear scalarization, i.e., combining all loss functions by a weighted sum, has been the default choice in the literature of multi-task learning (MTL) since its inception. In recent years, there is a surge of interest in developing Specialized Multi-Task Optimizers (SMTOs) that treat MTL as a multi-objective optimization problem. However, it remains open whether there is a fundamental advantage of SMTOs over scalarization. In fact, heated debates exist in the community comparing these two types of algorithms, mostly from an empirical perspective. To approach the above question, in this paper, we revisit scalarization from a theoretical perspective. We focus on linear MTL models and study whether scalarization is capable of fully exploring the Pareto front. Our findings reveal that, in contrast to recent works that claimed empirical advantages of scalarization, scalarization is inherently incapable of full exploration, especially for those Pareto optimal solutions that strike the balanced trade-offs between multiple tasks. More concretely, when the model is under-parametrized, we reveal a multi-surface structure of the feasible region and identify necessary and sufficient conditions for full exploration. This leads to the conclusion that scalarization is in general incapable of tracing out the Pareto front. Our theoretical results partially answer the open questions in Xin et al. (2021), and provide a more intuitive explanation on why scalarization fails beyond non-convexity. We additionally perform experiments on a real-world dataset using both scalarization and state-of-the-art SMTOs. The experimental results not only corroborate our theoretical findings, but also unveil the potential of SMTOs in finding balanced solutions, which cannot be achieved by scalarization.Comment: Accepted at NeurIPS 202

Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive Privacy Analysis and Beyond

We consider vertical logistic regression (VLR) trained with mini-batch gradient descent -- a setting which has attracted growing interest among industries and proven to be useful in a wide range of applications including finance and medical research. We provide a comprehensive and rigorous privacy analysis of VLR in a class of open-source Federated Learning frameworks, where the protocols might differ between one another, yet a procedure of obtaining local gradients is implicitly shared. We first consider the honest-but-curious threat model, in which the detailed implementation of protocol is neglected and only the shared procedure is assumed, which we abstract as an oracle. We find that even under this general setting, single-dimension feature and label can still be recovered from the other party under suitable constraints of batch size, thus demonstrating the potential vulnerability of all frameworks following the same philosophy. Then we look into a popular instantiation of the protocol based on Homomorphic Encryption (HE). We propose an active attack that significantly weaken the constraints on batch size in the previous analysis via generating and compressing auxiliary ciphertext. To address the privacy leakage within the HE-based protocol, we develop a simple-yet-effective countermeasure based on Differential Privacy (DP), and provide both utility and privacy guarantees for the updated algorithm. Finally, we empirically verify the effectiveness of our attack and defense on benchmark datasets. Altogether, our findings suggest that all vertical federated learning frameworks that solely depend on HE might contain severe privacy risks, and DP, which has already demonstrated its power in horizontal federated learning, can also play a crucial role in the vertical setting, especially when coupled with HE or secure multi-party computation (MPC) techniques

Synthesis of TiC nanotube arrays and their excellent supercapacitor performance

Nanostructured metal carbides have numerous applications in catalysis and energy storage. However, directional construction remains a significant challenge. In this work, a novel strategy for the direct synthesis of nanostructured metal carbides using nanostructured metal oxides as the precursor is developed. TiO2 nanotube arrays (TiO2 NTAs) can be successfully transformed into TiC nanotube arrays (TiC NTAs) through electro-deoxidation and carbonization reactions in a low-temperature molten salt. TiC NTAs have a highly oriented and ordered array structure, which shows the advantages of large specific surface area, direct electron transport, and good chemical stability. Here, TiC NTA electrodes and PVA-H3PO4 electrolyte gel were assembled into a flexible quasi-solid-state supercapacitor to characterize their energy storage performance. The results show that the TiC NTA electrodes exhibit a high areal capacitance of 53.3 mF cm−2, excellent cycling stability, and mechanical flexibility. Moreover, the energy densities can reach 4.6 μW h cm−2 at a power density of 78.9 μW cm−2. This work provides a new strategy for the directed synthesis of nanostructured metal carbides and demonstrates the energy storage application potential of TiC NTAs. It is expected that this work will contribute to the development of the synthesis and application of nanostructured metal carbides

A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems

Neuromorphic electronics, an emerging field that aims for building electronic mimics of the biological brain, holds promise for reshaping the frontiers of information technology and enabling a more intelligent and efficient computing paradigm. As their biological brain counterpart, the neuromorphic electronic systems are complex, having multiple levels of organization. Inspired by David Marr's famous three-level analytical framework developed for neuroscience, the advances in neuromorphic electronic systems are selectively surveyed and given significance to these research endeavors as appropriate from the computational level, algorithmic level, or implementation level. Under this framework, the problem of how to build a neuromorphic electronic system is defined in a tractable way. In conclusion, the development of neuromorphic electronic systems confronts a similar challenge to the one neuroscience confronts, that is, the limited constructability of the low-level knowledge (implementations and algorithms) to achieve high-level brain-like (human-level) computational functions. An opportunity arises from the communication among different levels and their codesign. Neuroscience lab-on-neuromorphic chip platforms offer additional opportunity for mutual benefit between the two disciplines

Identification of newly developed advanced schistosomiasis with MALDI-TOF mass spectrometry and ClinProTools analysis

Cases of newly developed advanced schistosomiasis (NDAS) have occurred in areas where schistosomiasis transmission has been blocked for more than 25 years. The causes and pathogenesis of NDAS are still unknown. Diagnosis of NDAS relies on historical investigation and clinical symptoms, such as liver fibrosis, hepatic ascites and abnormal biochemical indexes in serum. It is important but difficult at this stage to develop a new tool for early screening and rapid diagnosis. In this study, serum peptides from thirty patients with NDAS and thirty healthy controls were captured with weak cation exchange magnetic beads, and subjected to MALDI-TOF mass spectrometry and ClinProTools analysis. Eleven peaks with m/z 924, 2661, 2953, 2991, 3241, 3884, 5337, 5905, 5943, 7766 and 9289 were decreased and three peaks with m/z 1945, 2082 and 4282 were increased in the NDAS group. The proteomic detection pattern (PDP) was established with 14 different peptide peaks, and its sensitivity and specificity were investigated with a blind test. The peptide mass fingerprints of sera from 50 NDAS patients and 100 healthy controls were double-blind subjected to the PDP method, and 50 patients and 92 healthy controls were classified as NDAS and healthy separately, which showed 100% sensitivity and 92% specificity. Our results showed that the PDP could be a new and useful method to detect NDAS

Prediction of body fat increase from food addiction scale in school-aged children and adolescents: A longitudinal cross-lagged study

ObjectiveFood addiction (FA) is associated with a higher body mass index z-score (BMIZ) in children and adolescents; however, whether these two aspects evolve interdependently remains unknown. This study aimed to address this question using a cross-lagged study.MethodsWeight status, including BMIZ, fat content (FC), and visceral fat level (VFL), was determined in 880 children and adolescents (mean age = 14.02 years [range = 8.83–17.52 years]) at two-time points with an interval of 6 months. FA was characterized using the Chinese version of the dimensional Yale Food Addiction Scale for Children 2.0. Furthermore, FC and VFL were measured using direct segmental multi-frequency bioelectrical impedance analysis at each time point.ResultsHigher FA was associated with increased BMIZ, FC, and VFL (P < 0.05). FA at T0 could predict increased FC at T1 (P < 0.05). The characteristics of females, primary students, and living in urban areas may aggravate the adverse effect of FA on weight status over time and age, particularly the increased VFL in participants aged > 14 years.ConclusionChildren and adolescents with a high FA level were at risk for weight gain attributed to increased FC, and the adverse effect could be aggravated with time and age. Novel FA-targeting interventions may help mitigate the risk of getting obesity

A new species of Nanhsiungchelys (Testudines: Cryptodira: Nanhsiungchelyidae) from the Upper Cretaceous of Nanxiong Basin, China

Nanhsiungchelyidae are a group of large turtles that lived in Asia and North America during the Cretaceous. Here we report a new species of nanhsiungchelyid, Nanhsiungchelys yangi sp. nov., from the Upper Cretaceous of Nanxiong Basin, China. The specimen consists of a well-preserved skull and lower jaw, as well as the anterior parts of the carapace and plastron. The diagnostic features of Nanhsiungchelys include a large entire carapace length (∼55.5 cm), a network of sculptures consisting of pits and ridges on the surface of the skull and shell, shallow cheek emargination and temporal emargination, deep nuchal emargination, and a pair of anterolateral processes on the carapace. However, Nanhsiungchelys yangi differs from the other species of Nanhsiungchelys mainly in having a triangular-shaped snout (in dorsal view) and wide anterolateral processes on the carapace. Additionally, some other characteristics (e.g., the premaxilla is higher than wide, the maxilla is unseen in dorsal views, a small portion of the maxilla extends posterior and ventral of the orbit, and the parietal is bigger than the frontal) are strong evidence to distinguish Nanhsiungchelys yangi from Nanhsiungchelys wuchingensis. A phylogenetic analysis of nanhsiungchelyids places Nanhsiungchelys yangi and Nanhsiungchelys wuchingensis as sister taxa. Nanhsiungchelys yangi and some other nanhsiungchelyids bear distinct anterolateral processes on the carapace, which have not been reported in any extant turtles and may have played a role in protecting the head. The Nanxiong Basin was extremely hot during the Late Cretaceous, and so we suggest that nanhsiungchelyids might have immersed themselves in mud or water to avoid the heat, similar to some extant tortoises. If they were capable of swimming, our computer simulations of fluid flow suggest the anterolateral processes could have reduced drag during locomotion

Phase boundary engineering of metal-organic-framework-derived carbonaceous nickel selenides for sodium-ion batteries

Abstract: Sodium-ion batteries (SIBs) are promising power sources due to the low cost and abundance of battery-grade sodium resources, while practical SIBs suffer from intrinsically sluggish diffusion kinetics and severe volume changes of electrode materials. Metal-organic framework (MOFs) derived carbonaceous metal compound offer promising applications in electrode materials due to their tailorable composition, nanostructure, chemical and physical properties. Here, we fabricated hierarchical MOF-derived carbonaceous nickel selenides with bi-phase composition for enhanced sodium storage capability. As MOF formation time increases, the pyrolyzed and selenized products gradually transform from a single-phase Ni3Se4 into bi-phase NiSex then single-phase NiSe2, with concomitant morphological evolution from solid spheres into hierarchical urchin-like yolk-shell structures. As SIBs anodes, bi-phase NiSex@C/CNT-10h (10 h of hydrothermal synthesis time) exhibits a high specific capacity of 387.1 mAh/g at 0.1 A/g, long cycling stability of 306.3 mAh/g at a moderately high current density of 1 A/g after 2,000 cycles. Computational simulation further proves the lattice mismatch at the phase boundary facilitates more interstitial space for sodium storage. Our understanding of the phase boundary engineering of transformed MOFs and their morphological evolution is conducive to fabricate novel composites/hybrids for applications in batteries, catalysis, sensors, and environmental remediation