October 1, 2020 Machine Learning, SELF-DRIVING CARS

Artificial Intelligence in Surgery: Neural Networks and Deep Learning

Deep neural networks power most recent successes of artificial intelligence, spanning from self-driving cars to computer aided diagnosis in radiology and pathology. The high-stake data intensive process of surgery could highly benefit from such computational methods… However, surgeons and computer scientists should partner to develop and assess deep learning applications of value to patients and healthcare systems. This chapter and the accompanying hands-on material were designed for surgeons willing to understand the intuitions behind neural networks, become familiar with deep […]

October 1, 2020 Machine Learning, QUANTIZATION

Rotated Binary Neural Network

Binary Neural Network (BNN) shows its predominance in reducing the complexity of deep neural networks. However, it suffers severe performance degradation… One of the major impediments is the large quantization error between the full-precision weight vector and its binary vector. Previous works focus on compensating for the norm gap while leaving the angular bias hardly touched. In this paper, for the first time, we explore the influence of angular bias on the quantization error and then introduce a Rotated Binary […]

October 1, 2020 Machine Learning, TOPIC MODELS

AOBTM: Adaptive Online Biterm Topic Modeling Method for Version Sensitive Short-texts Analysis

Analysis of mobile app reviews has shown its important role in requirement engineering, software maintenance, and the evolution of mobile apps. Mobile app developers check their users’ reviews frequently to clarify the issues experienced by users or capture the new issues that are introduced due to a recent app update… App reviews have a dynamic nature and their discussed topics change over time. The changes in the topics among collected reviews for different versions of an app can reveal important […]

October 1, 2020 CONTRASTIVE LEARNING, Machine Learning

G-SimCLR: Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling

In the realms of computer vision, it is evident that deep neural networks perform better in a supervised setting with a large amount of labeled data. The representations learned with supervision are not only of high quality but also helps the model in enhancing its accuracy… However, the collection and annotation of a large dataset are costly and time-consuming. To avoid the same, there has been a lot of research going on in the field of unsupervised visual representation learning […]

October 1, 2020 DIALOGUE UNDERSTANDING, Machine Learning

Utterance-level Dialogue Understanding: An Empirical Study

The recent abundance of conversational data on the Web and elsewhere calls for effective NLP systems for dialog understanding. Complete utterance-level understanding often requires context understanding, defined by nearby utterances… In recent years, a number of approaches have been proposed for various utterance-level dialogue understanding tasks. Most of these approaches account for the context for effective understanding. In this paper, we explore and quantify the role of context for different aspects of a dialogue, namely emotion, intent, and dialogue act […]

October 1, 2020 Neural Machine Translation (NMT), NMT Leave a comment

Machine Translation Weekly 43: Dynamic Programming Encoding

One of the narratives people (including me) love to associate with neural machine translation is that we got rid of all linguistic assumptions about the text and let the neural network learn their own way independent of what people think about language. It sounds cool, it almost gives a science-fiction feeling. What I think that we really do is that we move our assumptions about language from hard constrains of discrete representation into soft constraints of inductive biases that we […]

October 1, 2020 Artificial intelligence Leave a comment

Archai can design your neural network with state-of-the-art neural architecture search (NAS)

The goal of neural architecture search (NAS) is to have computers automatically search for the best-performing neural networks. Recent advances in NAS methods have made it possible to build problem-specific networks that are faster, more compact, and less power hungry than their handcrafted counterparts. Unfortunately, many NAS methods rely on an array of tricks that aren’t always documented in a way that’s easy to discover. While these tricks result in neural networks with greater accuracy, they often cloud the performance […]

September 30, 2020 IMAGE SUPER-RESOLUTION, Machine Learning

Residual Feature Distillation Network for Lightweight Image Super-Resolution

Recent advances in single image super-resolution (SISR) explored the power of convolutional neural network (CNN) to achieve a better performance. Despite the great success of CNN-based methods, it is not easy to apply these methods to edge devices due to the requirement of heavy computation… To solve this problem, various fast and lightweight CNN models have been proposed. The information distillation network is one of the state-of-the-art methods, which adopts the channel splitting operation to extract distilled features. However, it […]

September 30, 2020 ADVERSARIAL ATTACK, Machine Learning

Improving Query Efficiency of Black-box Adversarial Attack

Deep neural networks (DNNs) have demonstrated excellent performance on various tasks, however they are under the risk of adversarial examples that can be easily generated when the target model is accessible to an attacker (white-box setting). As plenty of machine learning models have been deployed via online services that only provide query outputs from inaccessible models (e.g. Google Cloud Vision API2), black-box adversarial attacks (inaccessible target model) are of critical security concerns in practice rather than white-box ones… However, existing […]

September 30, 2020 CHATBOT, Machine Learning

Developing FB Chatbot Based on Deep Learning Using RASA Framework for University Enquiries

Smart systems for Universities powered by Artificial Intelligence have been massively developed to help humans in various tasks. The chatbot concept is not something new in today society which is developing with recent technology… College students or candidates of college students often need actual information like asking for something to customer service, especially during this pandemic, when it is difficult to have an immediate face-to-face meeting. Chatbots are functionally helping in several things such as curriculum information, admission for new […]

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