Deep Metric Loss for Multimodal Learning

Multimodal learning often outperforms its unimodal counterparts by exploiting unimodal contributions and cross-modal interactions. However, focusing only on integrating multimodal features into a unified comprehensive representation overlooks the unimodal characteristics. In real data, the contributions of modalities can vary from instance to instance, and they often reinforce or conflict with each other. In this study, we introduce a novel \text{MultiModal} loss paradigm for multimodal learning, which subgroups instances according to their unimodal contributions. \text{MultiModal} loss can prevent inefficient learning caused by overfitting and efficiently optimize multimodal models. On synthetic data, \text{MultiModal} loss demonstrates improved classification performance by subgrouping difficult instances within certain modalities. On four real multimodal datasets, our loss is empirically shown to improve the performance of recent models. Ablation studies verify the effectiveness of our loss. Additionally, we show that our loss generates a reliable prediction score for each modality, which is essential for subgrouping. Our \text{MultiModal} loss is a novel loss function to subgroup instances according to the contribution of modalities in multimodal learning and is applicable to a variety of multimodal models with unimodal decisions. Our code is available at https://github.com/SehwanMoon/MultiModalLoss.Comment: 18 pages, 9 figure

Reinvestigating the Relationship between Information Technology Capability and Firm Performance: Focusing On the Impact of the Adoption of Enterprise Systems

Though many information systems researchers have made various attempts to investigate the relationship between information technology capability and firm performance from diverse perspectives, we have not come to a conclusion yet with some mixed results. In this research, focusing on the adoption of Enterprise Resource Planning systems by firms as a proxy measure of information technology capability, we re-examine whether the association is positive or negative. With the sample of Korean firms which have adopted Enterprise Resource Planning (ERP) systems in 2009, we match ERP adopters and non-adopters with propensity score matching, and compare financial performance between them with difference-in-difference estimation between pre- and post-adoption period. According to our analysis, we find out that there is no positive and significant relationship between information technology capability and firm performance in profit ratios. This research shows that contrary to the era of propriety information systems, standardized information systems make no more competitive advantages against competitors these days

Information-Theoretic GAN Compression with Variational Energy-based Model

We propose an information-theoretic knowledge distillation approach for the compression of generative adversarial networks, which aims to maximize the mutual information between teacher and student networks via a variational optimization based on an energy-based model. Because the direct computation of the mutual information in continuous domains is intractable, our approach alternatively optimizes the student network by maximizing the variational lower bound of the mutual information. To achieve a tight lower bound, we introduce an energy-based model relying on a deep neural network to represent a flexible variational distribution that deals with high-dimensional images and consider spatial dependencies between pixels, effectively. Since the proposed method is a generic optimization algorithm, it can be conveniently incorporated into arbitrary generative adversarial networks and even dense prediction networks, e.g., image enhancement models. We demonstrate that the proposed algorithm achieves outstanding performance in model compression of generative adversarial networks consistently when combined with several existing models.Comment: Accepted at Neurips202

Exact Algorithm for the Capacitated Team Orienteering Problem with Time Windows

The capacitated team orienteering problem with time windows (CTOPTW) is a problem to determine players' paths that have the maximum rewards while satisfying the constraints. In this paper, we present the exact solution approach for the CTOPTW which has not been done in previous literature. We show that the branch-and-price (B&P) scheme which was originally developed for the team orienteering problem can be applied to the CTOPTW. To solve pricing problems, we used implicit enumeration acceleration techniques, heuristic algorithms, and ng-route relaxations

Diagnosis of Fault Modes Masked by Control Loops with an Application to Autonomous Hovercraft Systems

This paper introduces a methodology for the design, testing and assessment of incipient failure detection techniques for failing components/systems of an autonomous vehicle masked or hidden by feedback control loops. It is recognized that the optimum operation of critical assets (aircraft, autonomous systems, etc.) may be compromised by feedback control loops by masking severe fault modes while compensating for typical disturbances. Detrimental consequences of such occurrences include the inability to detect expeditiously and accurately incipient failures, loss of control and inefficient operation of assets in the form of fuel overconsumption and adverse environmental impact. We pursue a systems engineering process to design, construct and test an autonomous hovercraft instrumented appropriately for improved autonomy. Hidden fault modes are detected with performance guarantees by invoking a Bayesian estimation approach called particle filtering. Simulation and experimental studies are employed to demonstrate the efficacy of the proposed methods

Long-term survival benefits of intrathecal autologous bone marrow-derived mesenchymal stem cells (Neuronata-R®: lenzumestrocel) treatment in ALS: Propensity-score-matched control, surveillance study

ObjectiveNeuronata-R® (lenzumestrocel) is an autologous bone marrow-derived mesenchymal stem cell (BM-MSC) product, which was conditionally approved by the Korean Ministry of Food and Drug Safety (KMFDS, Republic of Korea) in 2013 for the treatment of amyotrophic lateral sclerosis (ALS). In the present study, we aimed to investigate the long-term survival benefits of treatment with intrathecal lenzumestrocel.MethodsA total of 157 participants who received lenzumestrocel and whose symptom duration was less than 2 years were included in the analysis (BM-MSC group). The survival data of placebo participants from the Pooled-Resource Open-Access ALS Clinical Trials (PROACT) database were used as the external control, and propensity score matching (PSM) was used to reduce confounding biases in baseline characteristics. Adverse events were recorded during the entire follow-up period after the first treatment.ResultsSurvival probability was significantly higher in the BM-MSC group compared to the external control group from the PROACT database (log-rank, p < 0.001). Multivariate Cox proportional hazard analysis showed a significantly lower hazard ratio for death in the BM-MSC group and indicated that multiple injections were more effective. Additionally, there were no serious adverse drug reactions found during the safety assessment, lasting a year after the first administration.ConclusionThe results of the present study showed that lenzumestrocel treatment had a long-term survival benefit in real-world ALS patients

Pravastatin Attenuates Acute Radiation-Induced Enteropathy and Improves Epithelial Cell Function

Background and Aim: Radiation-induced enteropathy is frequently observed after radiation therapy for abdominal and pelvic cancer or occurs secondary to accidental radiation exposure. The acute effects of irradiation on the intestine might be attributed to inhibition of mitosis in the crypts, as the loss of proliferative functions impairs development of the small intestinal epithelium and its barrier function. Especially, oxidative damage to intestinal epithelial cells is a key event in the initiation and progression of radiation-induced enteropathy. Pravastatin is widely used clinically to lower serum cholesterol levels and has been reported to have anti-inflammatory effects on endothelial cells. Here, we investigated the therapeutic effects of pravastatin on damaged epithelial cells after radiation-induced enteritis using in vitro and in vivo systems.Materials and Methods: To evaluate the effects of pravastatin on intestinal epithelial cells, we analyzed proliferation and senescence, oxidative damage, and inflammatory cytokine expression in an irradiated human intestinal epithelial cell line (InEpC). In addition, to investigate the therapeutic effects of pravastatin in mice, we performed histological analysis, bacterial translocation assays, and intestinal permeability assays, and also assessed inflammatory cytokine expression, using a radiation-induced enteropathy model.Results: Histological damage such as shortening of villi length and impaired intestinal crypt function was observed in whole abdominal-irradiated mice. However, damage was attenuated in pravastatin-treated animals, in which normalization of intestinal epithelial cell differentiation was also observed. Using in vitro and in vivo systems, we also showed that pravastatin improves the proliferative properties of intestinal epithelial cells and decreases radiation-induced oxidative damage to the intestine. In addition, pravastatin inhibited levels of epithelial-derived inflammatory cytokines including IL-6, IL-1β, and TNF-α in irradiated InEpC cells. We also determined that pravastatin could rescue intestinal barrier dysfunction via anti-inflammatory effects using the mouse model.Conclusion: Pravastatin has a therapeutic effect on intestinal lesions and attenuates radiation-induced epithelial damage by suppressing oxidative stress and the inflammatory response