Andrew Ng. This list is generated from documents in the CiteSeer x database as of March 19, 2015. Description: Decision Trees are a common learning algorithm and a decision representation tool. It will surprise few that methods papers lead the list of the most cited scientific articles ever—at least those tracked in the Institute for Scientific Information’s Science Citation Index, 1955 to 1987. The experiments demonstrate that the new model outperforms both BERT and Transformer-XL and achieves state-of-the-art performance on 18 NLP tasks. The experiments demonstrate the effectiveness of this approach with TRADE achieving state-of-the-art joint goal accuracy of 48.62% on a challenging MultiWOZ dataset. Currently, it is possible to estimate the shape of hidden, non-line-of-sight (NLOS) objects by measuring the intensity of photons scattered from them. The meta-objective directly reflects the usefulness of a representation generated from unlabeled data for further supervised tasks. The current research can significantly improve the performance of task-oriented dialogue systems in multi-domain settings. Machine learning, especially its subfield of Deep Learning, had many amazing advances in the recent years, and important research papers may lead to breakthroughs in technology that get used by billions of people. This is the course for which all other machine learning courses are judged. CV is the weighted average number of citations per year over the last 3 years. The top two papers have by far the highest citation counts than the rest. Trying out pruning methods other than sparse pruning. We believe our work is a significant advance over the state-of-the-art in non-line-of-sight imaging. To ensure automatic control over the warmup behavior, the researchers introduce a new variant of Adam, called Rectified Adam (RAdam). Introducing a meta-learning approach with an inner loop consisting of unsupervised learning. The new model achieves state-of-the-art performance on 18 NLP tasks including question answering, natural language inference, sentiment analysis, and document ranking. ... Or a slightly more recent citation to LeCun et al. Stabilizing the Lottery Ticket Hypothesis, as suggested in the researchers’. Demonstrating that social influence reward eventually leads to significantly higher collective reward and allows agents to learn meaningful communication protocols when this is otherwise impossible. The year 2019 saw an increase in the number of submissions. Artificial Intelligence in Modern Learning System : E-Learning. Most Cited Computer Science Articles. EndNote: Find the style here: output styles overview: Mendeley, Zotero, Papers, and others: The style is either built in or you can download a CSL file that is supported by most references management programs. Our results suggest that future work on disentanglement learning should be explicit about the role of inductive biases and (implicit) supervision, investigate concrete benefits of enforcing disentanglement of the learned representations, and consider a reproducible experimental setup covering several data sets. Abstract: Machine learning (ML) is a fast-growing topic that enables the extraction of patterns from varying types of datasets, ranging from medical data to financial data. HIC that presents how publications build upon and relate to each other is result of identifying meaningful citations. To overcome over-dependence on domain ontology and lack of knowledge sharing across domains, the researchers suggest: generating slot values directly instead of predicting the probability of every predefined ontology term; sharing all the model parameters across domains. A curated list of the most cited deep learning papers (2012-2016) We believe that there exist classic deep learning papers which are worth reading regardless of their application domain. We propose a unified mechanism for achieving coordination and communication in Multi-Agent Reinforcement Learning (MARL), through rewarding agents for having causal influence over other agents’ actions. We further propose RAdam, a new variant of Adam, by introducing a term to rectify the variance of the adaptive learning rate. Causal influence is assessed using counterfactual reasoning. The researchers generated so-called “winning ticket” networks, which are equal in accuracy to their parent networks at 10-20% of the size, by iteratively training, pruning, and re-initializing a neural network. > Machine learning is the science of credit assignment. Most Cited Computer Science Articles. CiteScore: 9.0 ℹ CiteScore: 2019: 9.0 CiteScore measures the average citations received per peer-reviewed document published in this title. Researchers from Google Brain and the University of California, Berkeley, sought to use meta-learning to tackle the problem of unsupervised representation learning. From what I seeing in most recent papers from the machine learning community, people (righteously, I believe) assume that the reader will know what this is and don't even include a general reference to conv nets. However, relying on corrupting the input with masks, BERT neglects dependency between the masked positions and suffers from a pretrain-finetune discrepancy. Random seeds and hyperparameters often matter more than the model but tuning seems to require supervision. Volume 20, Issue 1 January 2019. Photo by Dan Dimmock on Unsplash. The artificial intelligence sector sees over 14,000 papers published each year. The theoretical findings are supported by the results of a large-scale reproducible experimental study, where the researchers implemented six state-of-the-art unsupervised disentanglement learning approaches and six disentanglement measures from scratch on seven datasets: Even though all considered methods ensure that the individual dimensions of the aggregated posterior (which is sampled) are uncorrelated, the dimensions of the representation (which is taken to be the mean) are still correlated. Given a collection of Fermat pathlengths, the procedure produces an oriented point cloud for the NLOS surface. For every neural network, there is a smaller subset of nodes that can be used in isolation to achieve the same accuracy after training. Fermat paths correspond to discontinuities in the transient measurements. Andrew Ng is probably the most recognizable name in this list, at least to machine learning enthusiasts. A major goal of unsupervised learning is to discover data representations that are useful for subsequent tasks, without access to supervised labels during training. Specifically, we target semi-supervised classification performance, and we meta-learn an algorithm — an unsupervised weight update rule – that produces representations useful for this task. Enhanced security from cameras or sensors that can “see” beyond their field of view. Be the FIRST to understand and apply technical breakthroughs to your enterprise. Furthermore, the suggested meta-learning approach can be generalized across input data modalities, across permutations of the input dimensions, and across neural network architectures. 10 Important Research Papers In Conversational AI From 2019, 10 Cutting-Edge Research Papers In Computer Vision From 2019, Top 12 AI Ethics Research Papers Introduced In 2019, Breakthrough Research In Reinforcement Learning From 2019, Novel AI Approaches For Marketing & Advertising, 2020’s Top AI & Machine Learning Research Papers, GPT-3 & Beyond: 10 NLP Research Papers You Should Read, Novel Computer Vision Research Papers From 2020, Key Dialog Datasets: Overview and Critique. Create and source the Best of Applied artificial intelligence designed for learning how to cite in APA.! Doesn ’ t require a predefined ontology, which are shared across most cited machine learning papers! 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