Learning in Imperfect Environment: Multi-Label Classification with Long-Tailed Distribution and Partial Labels

Conventional multi-label classification (MLC) methods assume that all samples are fully labeled and identically distributed. Unfortunately, this assumption is unrealistic in large-scale MLC data that has long-tailed (LT) distribution and partial labels (PL). To address the problem, we introduce a novel task, Partial labeling and Long-Tailed Multi-Label Classification (PLT-MLC), to jointly consider the above two imperfect learning environments. Not surprisingly, we find that most LT-MLC and PL-MLC approaches fail to solve the PLT-MLC, resulting in significant performance degradation on the two proposed PLT-MLC benchmarks. Therefore, we propose an end-to-end learning framework: \textbf{CO}rrection $\rightarrow$ \textbf{M}odificat\textbf{I}on $\rightarrow$ balan\textbf{C}e, abbreviated as \textbf{\method{}}. Our bootstrapping philosophy is to simultaneously correct the missing labels (Correction) with convinced prediction confidence over a class-aware threshold and to learn from these recall labels during training. We next propose a novel multi-focal modifier loss that simultaneously addresses head-tail imbalance and positive-negative imbalance to adaptively modify the attention to different samples (Modification) under the LT class distribution. In addition, we develop a balanced training strategy by distilling the model's learning effect from head and tail samples, and thus design a balanced classifier (Balance) conditioned on the head and tail learning effect to maintain stable performance for all samples. Our experimental study shows that the proposed \method{} significantly outperforms general MLC, LT-MLC and PL-MLC methods in terms of effectiveness and robustness on our newly created PLT-MLC datasets

Packing Tree Degree Sequences

Special cases of the edge disjoint realizations of two tree degree sequences are considered in this paper. We show that if there is no node which have degree one in both degree sequences, then they always have edge-disjoint caterpillar realizations. By using a probabilistic method, we prove that two tree degree sequences always have edge-disjoint realizations if each vertex is a leaf in at least one of the trees. We also show that the edge-disjoint realization problem is in P for an arbitrary number of tree sequences with the property that each vertex is a non-leaf in at most one of the trees. On the other hand, we show that the following problem is already NP-complete: given two graphical degree sequences D-1 and D-2 such that D-2 is a tree degree sequence, decide if there exist edge-disjoint realizations of D-1 and D-2 where the realization of D-2 does not need to be a tree. Finally, we show that efficient approximations for the number of solutions as well as an almost uniform sampler exist for two tree degree sequences if each vertex is a leaf in at least one of the trees

From Plate to Prevention: A Dietary Nutrient-aided Platform for Health Promotion in Singapore

Singapore has been striving to improve the provision of healthcare services to her people. In this course, the government has taken note of the deficiency in regulating and supervising people's nutrient intake, which is identified as a contributing factor to the development of chronic diseases. Consequently, this issue has garnered significant attention. In this paper, we share our experience in addressing this issue and attaining medical-grade nutrient intake information to benefit Singaporeans in different aspects. To this end, we develop the FoodSG platform to incubate diverse healthcare-oriented applications as a service in Singapore, taking into account their shared requirements. We further identify the profound meaning of localized food datasets and systematically clean and curate a localized Singaporean food dataset FoodSG-233. To overcome the hurdle in recognition performance brought by Singaporean multifarious food dishes, we propose to integrate supervised contrastive learning into our food recognition model FoodSG-SCL for the intrinsic capability to mine hard positive/negative samples and therefore boost the accuracy. Through a comprehensive evaluation, we present performance results of the proposed model and insights on food-related healthcare applications. The FoodSG-233 dataset has been released in https://foodlg.comp.nus.edu.sg/

Rigorous Ab-Initio Modeling in Microscopy: a fast, stable and provable algorithm to estimate 3D molecular structure from uniformly oriented 2D projection images

Single particle reconstruction (SPR) using cryo-electron microscopy (cryo-EM) is a popular technique for determining the 3D structure of macro-molecular complexes from noisy 2D tomographic images taken at random viewing directions. Many mainstream algorithms start with an initial guess of the structure and iteratively refine this using the images. Such algorithms’ performance is often heavily dependent on the quality of the initial structure, necissitating an efficient algorithm to compute a good ab-initio estimate of the molecular structure. Recently, there has been a resurgence of effort to use Zvi Kam’s autocorrelation analysis to obtain such an estimate, under the assumption that the viewing directions of images are uniformly oriented. In Kam’s original paper from 1980, by estimating the second-order autocorrelation from images, the author shows that the expansion coefficients for the molecular structure are determined up to a sequence of missing orthogonal matrices. There have been attempts to recover these missing matrices from the third-order autocorrelation, but the computational process is often costly and lacks mathematical guarantees. In this paper, we provide a mathematical proof that, under certain explicit genericity conditions on the expansion coefficients, the third-order moment of images uniquely determines these orthogonal matrices up to the rotation and reflection of the molecule. In addition, we present an efficient algorithm called Orthogonal Matrix Retrieval via Backward Peeling and Forward Marching that computes these orthogonal matrices, recovering the analytic solution exactly in the case of noiseless moments. To our knowledge, ours is the first ab-initio algorithm with such a provable guarantee. The method exploits special structure in Kam’s moments to solve an over-determined system of multivariate polynomials by a certain nontrivial sequence of linear algebra computations. Numerical experiments are performed on synthetically generated data, establishing stability in the noisy moments case and confirming the competitive speed of our method in practice. The method exploits special structure in Kam’s moments to solve an over-determined system of multivariate polynomials by a certain nontrivial sequence of linear algebra computations. Numerical experiments are performed on synthetically generated data, establishing stability in the noisy moments case and confirming the competitive speed of our method in practice

Production of alpha-olefin in Acinetobacter baylyi ADP1

As energy and environmental issues become more and more serious, bioproduction of valuable chemicals, e.g. medium-chain alpha-olefins, as an alternative source become important increasingly. Medium-chain alpha-olefins, e.g. 1-undecene, are important hydrocarbon chemicals for various industrial applications. They can be used for industrial intermediates of detergents, cosmetic products, greases, lubricants, plasticizers, and “drop-in” next generation biofuel. Currently, medium-chain alpha-olefins are derived from fossil sources. This study demonstrated Acinetobacter baylyi ADP1 as an excellent biological engineering platform for the bioproduction of medium-chain alpha-olefins. An iron-dependent desaturase/decarboxylase UndA and a membrane-bound desaturase-like enzyme UndB can convert fatty acids to corresponding olefins. Glyoxylate shunt blocking was applied for A. baylyi ADP1 to optimize biosynthesis of 1-undecene, the 1-undecene production titer of 350 ng/ml was obtained by the expression of UndA. Biosynthesis system based on UndB produced 331 ng/ml of 1-undecene. Expression of UndB is feasible in A. baylyi ADP1, which can make ADP1 to produce wider range of olefins (including olefins with even number of carbon atoms: C12 and C14). This study demonstrated the potential of UndB in A. baylyi ADP1 and a possible 1-undecene biosynthesis rate limiting factor. The bioproduction of 1-undecene in A. baylyi ADP1 should be improved and optimized in further researches

BreathPro: Monitoring breathing mode during running with earables

Singapore Ministry of Education (MOE) Academic Research Fund (AcRF) Tier

Mental Health and Psychological Impact on Students with or without Hearing Loss during the Recurrence of the COVID-19 Pandemic in China

Background: This study compares the mental health and psychological response of students with or without hearing loss during the recurrence of the COVID-19 pandemic in Beijing, the capital of China. It explores the relevant factors affecting mental health and provides evidence-driven strategies to reduce adverse psychological impacts during the COVID-19 pandemic. Methods: We used the Chinese version of depression, anxiety, and stress scale 21 (DASS-21) to assess the mental health and the impact of events scale—revised (IES-R) to assess the COVID-19 psychological impact. Results: The students with hearing loss are frustrated with their disability and particularly vulnerable to stress symptoms, but they are highly endurable in mitigating this negative impact on coping with their well-being and responsibilities. They are also more resilient psychologically but less resistant mentally to the pandemic impacts than the students with normal hearing. Their mental and psychological response to the pandemic is associated with more related factors and variables than that of the students with normal hearing is. Conclusions: To safeguard the welfare of society, timely information on the pandemic, essential services for communication disorders, additional assistance and support in mental counseling should be provided to the vulnerable persons with hearing loss that are more susceptible to a public health emergency