## Simple Light Yet Formally Verified Global Common Subexpression Elimination and Loop Invariant Code Motion

We present an approach for implementing a formally certified loop-invariantcode motion optimization by composing an unrolling pass and an efficient global subexpression elimination . Each pass comes with a simple and independent proof ofcorrectness . The approach significantly narrows the performance gap between the CompCert certified compiler and state-of-the-art optimizingcompilers .…

## The Role of Time and Data Online Conformance Checking in the Manufacturing Domain

Manufacturing is a challenging domain that craves for process-oriented technologies to address digitalization challenges . Process mining creates high expectations, but its implementation and usage of it is unclear to a certain extent . The findings emphasize the importance of online conformance checking inmanufacturing and show how appropriate data sets can be identified andgenerated .…

## Automatic Learning to Detect Concept Drift

Active Drift Detection with Meta learning (Meta-ADD) is a novel framework that learns to classify concept drift by tracking the changed pattern of error rates . Meta-ADD uses machine learning to learn to detect concept drifts and identify their types automatically, which candirectly support drift understand .…

## An Overview of Laser Injection against Embedded Neural Network Models

The deployment of models in a large variety of devices faces several obstacles related to trust and security . Fault Injection Analysis (FIA) are known to be very powerful with a large spectrum of attack vectors . Laser injection with state-of-the-art equipment, combined with theoretical evidences from Adversarial Machine Learning, highlights worryingthreats against the integrity of deep learning inference and claims that joinefforts from the theoretical AI and Physical Security communities are a urgent need .…

## An Empirical Review of Deep Learning Frameworks for Change Detection Model Design Experimental Frameworks Challenges and Research Needs

Visual change detection is one of the elementary tasks in computervision and video analytics . Applications include anomaly detection, object tracking, traffic monitoring, human machine interaction, behavior analysis, action recognition, and visual surveillance . The challenges in change detection include background fluctuations,illumination variation, weather changes, intermittent object motion, shadow, camera motion, and heterogeneous object shapes .…

## Dual Cross Central Difference Network for Face Anti Spoofing

Face anti-spoofing (FAS) plays a vital role in securing face recognitionsystems . Central difference convolution (CDC) has shown its excellent capacity for the FAS task via leveraging local gradientfeatures . However, aggregating central difference clues from allneighbors/directions simultaneously makes CDC redundant and sub-optimized .…

## LAFFNet A Lightweight Adaptive Feature Fusion Network for Underwater Image Enhancement

There are many deep-learning-based methods with impressive performance for underwater image enhancement, but their memory and model parameter costs are hindrances in practical application . Toaddress this issue, we propose a lightweight adaptive feature fusion network(LAFFNet) The model is the encoder-decoder model with multiple adaptivefeature fusion (AAF) modules .…

## Technical Report for Valence Arousal Estimation on Affwild2 Dataset

In this work, we describe our method for tackling the valence-arousalestimation challenge from ABAW FG-2020 Competition . The competition organizers provide an in-the-wild Aff-Wild2 dataset for participants to analyze affectivebehavior in real-life settings . We use MIMAMO Net to achieve information about micro-motion and macro-motion for improving videoemotion recognition .…

## Collaborative Multi Resource Allocation in Terrestrial Satellite Network Towards 6G

Terrestrial-satellite networks are envisioned to play a significant role inthe sixth-generation (6G) wireless networks . In such networks, hot air balloons are useful as they can relay the signals between satellites and groundstations . Most existing works assume the same height with the same minimum elevation angle to the satellites, which may not be practical due to possible route conflict with airplanes and otherflight equipment .…

## Canonical Saliency Maps Decoding Deep Face Models

The Canonical Saliency Maps highlight facial features responsible for the decision made by a deep face model on a given image . Image-level maps highlight facialfeatures responsible for a DNN decision, thus helping to understand how a . DNN made a prediction on the image .…

## Weak Multi View Supervision for Surface Mapping Estimation

We propose a weakly-supervised multi-view learning approach to learn category-specific surface mapping without dense annotations . We learn theunderlying surface geometry of common categories, such as human faces, cars,and airplanes, given instances from those categories . Our approach leverages information from multiple views of the object to establish additional consistency cycles, thus improving surface mapping understanding .…

## Federated Multi View Learning for Private Medical Data Integration and Analysis

Medical data is naturally distributed across multiple sites, making it difficult to collectively train machine learning models without data leakage . In medical applications, data are oftencollected from different sources and views, resulting in heterogeneity and complexity that requires reconciliation .…

## Hallucination Improves Few Shot Object Detection

Learning to detect novel objects from few annotated examples is of greatpractical importance . A particularly challenging yet common regime occurs whenthere are extremely limited examples (less than three) One critical factor in improving few-shot detection is to address the lack of variation in training data .…

## YAPS Your Open Examination System for Activating and emPowering Students

There are numerous e-assessment systems devoted to specific domains underdiverse license models . Cost, extensibility, and maintainability are relevant issues for an institution . Ease of use and inclusion into courses are main concerns . For students the user experience and fast transparent feedback plus “better” tests are most important .…

## Defeating Super Reactive Jammers With Deception Strategy Modeling Signal Detection and Performance Analysis

This paper develops a novel framework to defeat a super-reactive jammer, one of the most difficult jamming attacks to deal with in practice . We introduce a smart deception mechanism to attract the jammer to continuously attack the channel and then leverage jamming signalsto transmit data based on the ambient backscatter communication technology .…

## Self Supervised Approach for Facial Movement Based Optical Flow

Deep learning-based optical flow techniques do not perform well for non-rigidmovements such as those found in faces . We hypothesize that learning opticalflow on face motion data will improve the quality of predicted flow on faces . The performance of FlowNetS trained on face images surpassed that of other opticalflow CNN architectures, demonstrating its usefulness.…

## Counting vertices of integer polytopes defined by facets

We present a number of complexity results concerning the problem of counting vertices of an integral polytope . The focus is on polytopes with small integer vertices, particularly 0/1polytopes .…

## Online Transfer Learning Negative Transfer and Effect of Prior Knowledge

Transfer learning is a machine learning paradigm where the knowledge from onetask is utilized to resolve the problem in a related task . In this paper, we study the online transfer learning problems where the sourcesamples are given in an offline way while the target samples arrive .…

## Data Efficient Reinforcement Learning for Malaria Control

The main challenge faced by policymakers is to learn a policy from scratch by interacting with a complex environment in a few trials . This work introduces apractical, data-efficient policy learning method, named Variance-Bonus MonteCarlo Tree Search~(VB-MCTS) It can copy with very little data andfacilitate learning from scratch in only a few trial times .…

## Effects of Quantization on the Multiple Round Secret Key Capacity

We consider the strong secret key (SK) agreement problem for the satellitecommunication setting . Legitimate receivers have access to an authenticated, noiseless, two-way, and public communication link . The noise variances for Alice’s and Bob’s measurement channels are both fixed to a value $Q1$, whereas the noise over Eve’s measurement channel has a unitvariance, so $Q$ represents a channel quality ratio .…

## Continuous indetermination and average likelihood minimization

Authors transpose a discrete notion of indetermination coupling in thecase of continuous probabilities . They show that this coupling, expressed ondensities, cannot be captured by a specific copula which acts on cumulativedistribution functions without a high dependence on the margins .…

## Autonomous Robotic Mapping of Fragile Geologic Features

Robotic mapping is useful in scientific applications that involve surveyingunstructured environments . This paper presents a target-oriented mapping system for sparsely distributed geologic surface features, such as precariouslybalanced rocks (PBRs), whose geometric fragility parameters can provide valuable information on earthquake shaking history and landscape development .…

## Walk in the Cloud Learning Curves for Point Clouds Shape Analysis

Discrete point cloud objects lack sufficient shape descriptors of 3Dgeometries . In this paper, we present a novel method for aggregatinghypothetical curves in point clouds . Sequences of connected points (curves) areinitially grouped by taking guided walks in the point clouds, and then aggregated back to augment their point-wise features .…

## The Pursuit of Knowledge Discovering and Localizing Novel Categories using Dual Memory

We tackle object category discovery, which is the problem of discovering andlocalizing novel objects in a large unlabeled dataset . We propose a method to use prior knowledge about certain object categories to discover new categories by leveraging twomemory modules, namely Working and Semantic memory .…

## Eigenfactor

The Eigenfactor is a journal metric, which was developed by Bergstrom and his colleagues at the University of Washington . It establishes the importance, influence or impact of a journal based on its location in a network of journals . While journal-basedmetrics have been criticized, it has also been suggested as analternative in the widely used San Francisco Declaration on Research Assessment(DORA) The algorithm is based on Eigenvector centrality, i.e.…

## QSOC Quantum Service Oriented Computing

Quantum computing is quickly turning from a promise to a reality, witnessing the launch of several cloud-based, general-purpose offerings, and IDEs . Quantum Service-Oriented Computing (QSOC) is a model-driven methodology to allow DevOps teams to compose, configure and operate enterprise applications without intimate knowledge on the underlying quantuminfrastructure .…

## MLP Mixer An all MLP Architecture for Vision

Convolutional Neural Networks (CNNs) are the go-to model for computer vision . Attention-based networks, such as the Vision Transformer, have also become popular . In this paper we show that while convolutions and attention are sufficient for good performance, neither of them are necessary .…

## HASCO Towards Agile HArdware and Software CO design for Tensor Computation

Tensor computations overwhelm traditional general-purpose computing devices . They callfor a holistic solution composed of both hardware acceleration and softwaremapping . Hardware/software (HW/SW) co-design optimizes the hardware andsoftware in concert and produces high-quality solutions . Hasco achieves a 1.25X to 1.44Xlatency reduction through HW/SW co-Design compared with developing the hardwareand software separately .…

## Small Sample Inferred Adaptive Recoding for Batched Network Coding

Batched network coding is a low-complexity network coding solution tofeedbackless multi-hop wireless packet network transmission with packet loss . Adaptiverecoding is a technique to adapt the fluctuation of packet loss by optimizing the number of recoded packets per batch to enhance the throughput .…