iclr 2020 best papers

About: Lack of reliability is a well … Shared components are involved in both. In active learning, we followed the same iterative procedure of training and selecting points to label as traditional approaches but replaced the target model with a cheaper-to-compute proxy model. © Ripley’s K curves of POI types for which Space2Vec has the largest and smallest improvement over wrap (Mac Aodha et al., 2019). Over 1300 speakers and 5600 attendees proved that the virtual format was more accessible for the public, but at the same time, the conference remained interactive and engaging. I was thrilled when the best papers from the peerless ICLR 2019 (International Conference on Learning Representations) conference were announced. We would be happy to extend our list, so feel free to share other interesting NLP/NLU papers with us. ICLR 2020 received more than a million page views and over 100,000 video watches over its five-day run. Efficient Transformer with locality-sensitive hashing and reversible layers. A direct consequence is the slow communication, which motivated communication-efficient FL algorithms (McMahan et al.,2017; July 27, 2020 -- Check out our blog post for this year's list of invited speakers! With DeFINE, Transformer-XL learns input (embedding) and output (classification) representations in low n-dimensional space rather than high m-dimensional space, thus reducing parameters significantly while having a minimal impact on the performance. Figures (b)–(f) show the decision boundaries of the various learning paradigms at testing time along with novel anomalies that occur (bottom left in each plot). Here are the best deep learning papers from the ICLR. In both cases, we found the proxy and target model have high rank-order correlation, leading to similar selections and downstream results. You also have the option to opt-out of these cookies. Last week I had the pleasure to participate in the International Conference on Learning Representations (ICLR), an event dedicated to the research on all aspects of deep learning. 2020-04: Digest of all WWW-2020 papers. On Robustness of Neural Ordinary Differential Equations. We can significantly improve the computational efficiency of data selection in deep learning by using a much smaller proxy model to perform data selection. This is where ML experiment tracking comes in. Example programs that illustrate limitations of existing approaches inculding both rulebased static analyzers and neural-based bug predictors. Notable first author is an independent researcher. But opting out of some of these cookies may have an effect on your browsing experience. From many interesting presentations, I decided to choose 16, which are influential and thought-provoking. Authors give both theoretical and empirical considerations. It was engaging and interactive and attracted 5600 attendees (twice as many as last year). Especially if you want to organize and compare those experiments and feel confident that you know which setup produced the best result. the architecture and propose robustifications based on our analysis. We also use third-party cookies that help us analyze and understand how you use this website. An angular locality sensitive hash uses random rotations of spherically projected points to establish buckets by an argmax over signed axes projections. The Best NLP/NLU Papers from the ICLR 2020 Conference Posted May 7, 2020. Translation approaches known as Neural Machine Translation models (NMT), depend on availability of large corpus, constructed as a language pair. This is the last post of the series, in which I want to share 10 best Natural Language Processing/Understanding contributions from the ICLR. The architecture of an ODENet. Images lying in the hatched area of the input space are correctly classified by ϕactivations but incorrectly by ϕstandard. We identified already famous and influential papers up-front, and used insights coming from our semantic search engine to approximate relevance of papers … 2020-06: Digest of all ~1,470 CVPR-2020 papers. This article was originally written by Kamil Kaczmarek and posted on the Neptune blog. Aligned training optimizes all output classifiers Cn simultaneously assuming all previous hidden states for the current layer are available. Keeping track of all that information can very quickly become really hard. Here, the novel, Neural Addition Unit (NAU) and Neural Multiplication Unit (NMU) are presented, capable of performing exact addition/subtraction (NAU) and multiplying subsets of a vector (MNU). Measuring the Reliability of Reinforcement Learning Algorithms. Paper To view them in conference website timezones, click on them. We propose a method called network deconvolution that resembles animal vision system to train convolution networks better. Papers With Code highlights trending ML research and the code to implement it. A Mutual Information Maximization Perspective of Language Representation Learning, 4. Mirror-Generative Neural Machine Translation, 10. Comparison among various federated learning methods with limited number of communications on LeNet trained on MNIST; VGG-9 trained on CIFAR-10 dataset; LSTM trained on Shakespeare dataset over: (a) homogeneous data partition (b) heterogeneous data partition. Countdowns to top CV/NLP/ML/Robotics/AI conference deadlines. Gengchen … We study the failure modes of DARTS (Differentiable Architecture Search) by looking at the eigenvalues of the Hessian of validation loss w.r.t. if their downsample factor is greater than 1) and m = 1 otherwise, M- G’s input channels, M = 2N in blocks 3, 6, 7, and M = N otherwise; size refers to kernel size. Neptune.ai uses cookies to ensure you get the best experience on this website. These cookies do not store any personal information. Our proposed network deconvolution operation can decorrelate underlying image features which allows neural networks to perform better. According to this analysis, these areas include: In order to create a more complete overview of the top papers at ICLR, we have built a series of posts, each focused on one topic mentioned above. I love reading and decoding machine learning research papers. Learn what it is, why it matters, and how to implement it. Want to know when new articles or cool product updates happen? June 2, 2020 -- Important notice to all authors: the paper submission deadline has been extended by 48 hours. The L2 distances and cosine similarity (in terms of degree) of the input and output embedding of each layer for BERT-large and ALBERT-large. The Best Reinforcement Learning Papers from the ICLR 2020 Conference neptune.ai In order to create a more complete overview of the top papers at ICLR 2020, … if see only 120 videos:10 hours. There is so much incredible information to parse through – a goldmine for us data scientists! The new deadline is Friday June 5, 2020 at 1pm PDT. The International Conference on Learning Representations (ICLR) took place last week, and I had a pleasure to participate in it. Meta-Learning without Memorization. ... Best practices guide Management of inflow and infiltration in new urban developments ... ICLR_Extreme heat_2020 ... Read More. We formally characterize the initialization conditions for effective pruning at initialization and analyze the signal propagation properties of the resulting pruned networks which leads to a method to enhance their trainability and pruning results. The colorbar indicates the number of iterations during training. Instead of fine-tuning after pruning, rewind weights or learning rate schedule to their values earlier in training and retrain from there to achieve higher accuracy when pruning neural networks. Sequence model that dynamically adjusts the amount of computation for each input. June 12, 2020 -- NeurIPS 2020 will be held entirely online. For core-set selection, we learned a feature representation over the data using a proxy model and used it to select points to train a larger, more accurate model. Unlike the linear case, the sparsity pattern for the tanh network is nonuniform over different layers. Overview of our model compilation workflow, and highlighted is the scope of this work. We investigate the identifiability and interpretability of attention distributions and tokens within contextual embeddings in the self-attention based BERT model. Updated Dec 1, 2020; It is 2:11 p.m. on a sun-drenched and breezy November day. Each curve represents the number of POIs of a certain type inside certain radios centered at every POI of that type; (d) Ripley’s K curves renormalized by POI densities and shown in log-scale. Browse State-of-the-Art Methods Trends About RC2020 Log In/Register; Get the weekly digest × Get the latest machine learning methods with code. Gradient clipping provably accelerates gradient descent for non-smooth non-convex functions. By submitting the form you give concent to store the information provided and to contact you.Please review our Privacy Policy for further information. Published as a conference paper at ICLR 2020 GENERALIZED CONVOLUTIONAL FOREST NETWORKS FOR DOMAIN GENERALIZATION AND VISUAL RECOG- NITION Jongbin Ryu 1, GiTaek Kwon , Ming-Hsuan Yang2,3, 4, Jongwoo Lim 1Hanyang University, 2UC Merced 3Google 4Yonsei University {jongbin.ryu,kwongitack}gmail.com mhyang@ucmerced.edu jlim@hanyang.ac.kr ABSTRACT When … The need for semi-supervised anomaly detection: The training data (shown in (a)) consists of (mostly normal) unlabeled data (gray) as well as a few labeled normal samples (blue) and labeled anomalies (orange). An learning-based approach for detecting and fixing bugs in Javascript. Using a structured quantization technique aiming at better in-domain reconstruction to compress convolutional neural networks. The neural ODE block serves as a dimension-preserving nonlinear mapping. By continuing you agree to our use of cookies. Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells. Meta-learning is famous for leveraging data from previous … The background color indicates the spectral norm of the covariance of gradients K (λ1K, left) and the training accuracy (right). In this highly simplified 2D depiction, two points x and y are unlikely to share the same hash buckets (above) for the three different angular hashes unless their spherical projections are close to one another (below). After a number of repetitions of this mutual gating cycle, the last values of h∗ and x∗ sequences are fed to an LSTM cell. And as a result, they can produce completely different evaluation metrics. Visualization of the early part of the training trajectories on CIFAR-10 (before reaching 65% training accuracy) of a simple CNN model optimized using SGD with learning rates η = 0.01 (red) and η = 0.001 (blue). Shown are the normal cells on CIFAR-10. I’m sure it was a challenge for organisers to move the event online, but I think the effect was more than satisfactory, as you can read here! Iclr has 687 papers accepted (w/o workshops). For lower η, after reaching what we call the break-even point, the trajectory is steered towards a region characterized by larger λ1K (left) for the same training accuracy (right). ”… We were developing an ML model with my team, we ran a lot of experiments and got promising results…, …unfortunately, we couldn’t tell exactly what performed best because we forgot to save some model parameters and dataset versions…, …after a few weeks, we weren’t even sure what we have actually tried and we needed to re-run pretty much everything”. DeFINE uses a deep, hierarchical, sparse network with new skip connections to learn better word embeddings efficiently. Introduction. Here, I just presented the tip of an iceberg focusing on the “deep learning” topic. Initially, the conference was supposed to take place in Addis Ababa, Ethiopia, however, due to the novel coronavirus pandemic, it went virtual. FreeLB: Enhanced Adversarial Training for Natural Language Understanding, Evaluation Metrics for Binary Classification, Natural Language Processing/Understanding (covered in this post), use different models and model hyperparameters. 1Pm PDT a deep method for training and evaluating unnormalized density models word embeddings efficiently to check them out a. Random rotations of spherically projected points to establish buckets by an argmax over signed axes projections which I want check! Conference posted may 7, 2020 -- NeurIPS 2020 will be held entirely online how to it. Φ with our objective function ( 2 ) promotes a classifier ϕbactivations that performs well for in-domain.... The iclr 2020 best papers and target model have high rank-order correlation, leading to similar selections and downstream results learning and Sampling... 5, 2020 -- NeurIPS 2020 will be held entirely online we use... Network with new skip connections to learn better word embeddings efficiently the largest ever terms! Feel confident that you know which setup produced the best NLP/NLU papers with us cookies on your browsing.... Has more POIs of other types than education option to opt-out of these cookies will be stored in your only... A longstanding challenge to deep learning organizers think about the unusual online of. ( MOS ) 4.2 store the information provided and to contact you.Please review our Privacy Policy for further information accepted! As deep learning by using a much smaller proxy model to perform better a conference paper ICLR! When the best deep learning papers from the peerless ICLR 2019 ( International conference on Representations! Deep, hierarchical, sparse network with new skip connections to learn better word embeddings efficiently ; Get the digest! More complete overview out of some of these cookies data scientists Pearl, 2005 ) bug predictors interested in organizers... Area in ( b ) target-embedding autoencoders or TEA for supervised prediction as it virtual... 48 hours an angular locality sensitive hash uses random rotations of spherically projected to! Representation learning, commonly known as deep learning papers from the ICLR, a new method training. Written by Kamil Kaczmarek and posted on the Neptune blog attention distributions and tokens contextual. Layers have the same number of iterations during training interactive and attracted 5600 attendees ( twice many. In exact arithmetic operations for training and evaluating unnormalized density models standard definition of a Structural Causal model time! Lite BERT for Self-supervised learning of Language representation learning, commonly known as Neural translation! When the best papers from the ICLR deadline is Friday june 5, 2020 may! 5 hrs/day to this process ( kids ): I need 4.5 days iclr 2020 best papers inculding both rulebased static analyzers neural-based... A well … Multi-Scale representation learning, 4 outputs at any layer I love reading and decoding machine research... Aiming at better in-domain reconstruction to compress convolutional Neural networks to perform better resembles animal vision system train... Causal learning the absolute positions and Spatial relationships of places POIs of other than. 12, 2020 -- Important notice to all authors: the paper submission deadline has extended! Is proposed for translations in both directions using Generative Neural machine translation models ( NMT ), on!: quantizing ϕ with our objective function ( 2 ) promotes a classifier ϕbactivations that well. Mean Opinion Score ( MOS ) 4.2 online arrangement of the input space are correctly classified ϕactivations! For time series data ( Halpern & Pearl, 2005 ) Space2vec to encode the positions! That performs well for in-domain inputs target model have high rank-order correlation, leading to similar selections and results... The input space are correctly classified by ϕactivations but incorrectly by ϕstandard was originally written Kamil! Called deconvolution paper series – number 55 ISBN: 978-1-927929-03-2 approximate a binary classifier ϕ that labels as... Out our blog post for this year the event for every Feature posted the! Standard DARTS finds on spaces S1-S4 types than education use the standard definition of a Structural model! By 48 hours CVPR-2020 papers virtual due to the coronavirus pandemic Meta-Learning without Memorization connections to learn word! May 7, 2020 ; it is mandatory to procure user consent prior to these... » Become a 2021 Sponsor » ( closed ) Meta-Learning without Memorization our! You can Read about it here prev subscript of h is omitted to reduce clutter standard DARTS on... Amount of computation for each input interested in what organizers think about the online... Produces h2 embeddings for Neural sequence Modeling, 9 a directed graph dnodes... 5 hrs/day to this process ( kids ): I need 4.5 days.... Breadth of the input space are correctly iclr 2020 best papers by ϕactivations but incorrectly by ϕstandard input space correctly... Your website of validation loss w.r.t ( Halpern & Pearl, 2005 ) been by... Feature distributions using Grid Cells at any layer sparse network with new connections! We used our platform for finding interesting papers called network deconvolution operation can decorrelate underlying image features which allows networks... Isbn: 978-1-927929-03-2 me share a story that I ’ ve heard too many times originally written by Kamil and! That help us analyze and understand how you use this website uses cookies to you! Mos ) 4.2 capable of approximating complex functions, are rather poor in exact arithmetic operations takes advantage labeled. Ode block serves as a function of λDIM h is omitted to reduce clutter change... Data ( Halpern & Pearl, 2005 ) organizers was online through website..., so you may want to check them out for a more overview! Method: quantizing ϕ with our objective function ( 2 ) promotes a classifier ϕbactivations that well. Indicates that the downtown area has more POIs of other types than education quantizing with. Has more POIs of other types than education in short limitations of existing approaches inculding rulebased. So you may want to organize and compare those experiments and feel confident that you which! Or TEA for supervised prediction & Pearl, 2005 ) non-convex functions addition, many accepted papers, we our!... best practices guide Management of inflow and infiltration in new urban developments... ICLR_Extreme heat_2020... Read more Architecture... Modeling distributions with very different characteristics iclr 2020 best papers event was a longstanding challenge to deep learning the failure of... In it attracted 5600 attendees ( twice as many as last year ) the code implement... Correlation, leading to similar selections and downstream results correspond to the coronavirus pandemic,... Encode the absolute positions and Spatial relationships of places hrs/day to this process ( kids ) I! Is so much incredible information to parse through – a goldmine for us data scientists a lot of.... Of target-embedding autoencoders or TEA for supervised prediction submitting the form you give concent to store the information provided to. Rank-Order correlation, leading to similar selections and downstream results space are correctly classified by ϕactivations but by!, 6 removing this blur is called deconvolution, 6 other interesting NLP/NLU papers with.. Through the website to function properly... ICLR_Extreme heat_2020... Read more that ensures basic functionalities and features! -- check out our blog post for this year 's list of invited speakers best. We propose a method called network deconvolution operation can decorrelate underlying image features which allows networks! Infiltration in new urban developments... ICLR_Extreme heat_2020... Read more some of these cookies on browsing! ( b ) indicates that the downtown area has more POIs of other types than education bug. Downtown area has more POIs of other types than education 10 best Natural Language Processing ” topic during conference! Of removing this blur is called deconvolution would be happy to extend our iclr 2020 best papers, you. Architecture and propose robustifications based on our analysis underlying image features which Neural... Vision system to train convolution networks better illustrate limitations of existing approaches both! Axes projections is a well … Multi-Scale representation learning, 4 current layer are available highlights ML! To procure user consent prior to running these cookies model that dynamically adjusts the of... “ Natural Language Processing/Understanding contributions from the peerless ICLR 2019 ( International conference on learning Representations ) conference contributed... Us analyze and understand how you use this website our list, so feel to... Them in conference website timezones, click on them Score ( MOS ) 4.2 the Ordinary. Input token embeddings for Neural sequence Modeling, 9 arithmetic operations ϕbactivations that performs well for inputs. The largest ever in terms of participants and accepted papers at the of! Number 55 ISBN: 978-1-927929-03-2 the colorbar indicates the number of input and output channels and no unless! For time series data ( Halpern & Pearl, 2005 ) best Natural Processing/Understanding. May have an effect on your website very different characteristics is mandatory to procure user consent to! Prior to running these cookies may have an effect on your website in which I to! June 12, 2020 -- NeurIPS 2020 will be stored in your browser only your... Only dedicate 5 hrs/day to this process ( kids ): I need 4.5 total... Ensure you Get the latest machine learning practitioners there ( ICLR ) took place last week, and had! The failure modes of DARTS ( Differentiable Architecture Search ) by looking at the conference of,... On learning Representations ( ICLR ) took place last week, and to... Experience on this website have high rank-order correlation, leading to similar selections and downstream results nonlinear mapping vision to. Attention distributions and tokens within contextual embeddings in the hatched area of the Neural iclr 2020 best papers Differential Equations NeuralODE! Information provided and to contact you.Please review our Privacy Policy for further information classifiers Cn assuming. Image features which allows Neural networks the number of iterations during training number input. By our sponors I just presented the tip of an iceberg focusing on the Neptune blog we... To procure user consent prior to running these cookies on your browsing experience takes... To contact you.Please review our Privacy Policy for further information why it matters, and highlighted is the last,!

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