Iclr 2020 best paper award

The ICLR virtual conference wrapped up this weekend, with generally favourable reviews from participants and a number of areas for future improvements identified by organizers. The ICLR yesterday made the entire virtual conference available in open-access, enabling anyone to access the content and explore the virtual conference portal.

The conference was originally scheduled for Addis Ababa, Ethiopia, but this aspect was cancelled on March Organizers made a number of adjustments to enable and encourage networking for conference participants, such as opening various virtual rooms and scheduling socials.

Each of the papers was presented by its authors through pre-recorded videos, and every paper was presented twice in two separate sessions considering global time zone differences. ICLR received more than a million page views and overvideo watches over its five-day run.

All posters were widely viewed as part of a live conference, with an average of unique views per paper page. The virtual conference created a new environment in which organizers were able to try out — albeit in a more rushed manner than they might have liked — many of the machine learning approaches that the conference itself showcases. The coverage of topics was also lacking, and organizers believe that given more time they could have made better calls for particular socials topics to facilitate improved interaction between attendees.

For future virtual conferences, the organizers also recommend pre-arranged video meet-and-greet sessions, mentorship programs, and even standing virtual coffee sessions, and hope the community can explore additional ways for improving interactivity. Great job! We're "back" from ICLR and are so impressed with all the papers, talks, and discussions all done virtually!

The organizers say ICLR will be held the first week of May, but it remains undecided whether this will be a physical or virtual conference or some combination of the two. Synced will provide updates as further information becomes available.

Notify me of follow-up comments by email. Notify me of new posts by email. Share this: Twitter Facebook. Like this: Like Loading Comment Name Email Website Notify me of follow-up comments by email. Previous Post. Next Post.Toggle navigation. In addition, many accepted papers at the conference were contributed by our sponors. The International Conference on Learning Representations ICLR is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.

ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.

Participants at ICLR span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs. A non-exhaustive list of relevant topics explored at the conference include:. Toggle navigation Toggle navigation Login. Year Tue May 4th through Sat the 8th. About Us The International Conference on Learning Representations ICLR is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.

A non-exhaustive list of relevant topics explored at the conference include: unsupervised, semi-supervised, and supervised representation learning representation learning for planning and reinforcement learning representation learning for computer vision and natural language processing metric learning and kernel learning sparse coding and dimensionality expansion hierarchical models optimization for representation learning learning representations of outputs or states implementation issues, parallelization, software platforms, hardware applications in audio, speech, robotics, neuroscience, computational biology, or any other field societal considerations of representation learning including fairness, safety, privacy.

Do not remove: This comment is monitored to verify that the site is working properly. Workshop Application Close.Toggle navigation. To recognize excellent work conducted by members of the ICML community, we have two types of awards. The test of time award is given to a paper from ICML ten years ago that has had substantial impact on the field of machine learning, including both research and practice.

The recipients of the Test of Time award will give a plenary talk at the following times on Monday July We formalize this task as a multiarmed bandit problem, where the payoff function is either sampled from a Gaussian process GP or has low RKHS norm.

We resolve the important open problem of deriving regret bounds for this setting, which imply novel convergence rates for GP optimization. We analyze GP-UCB, an intuitive upper-confidence based algorithm, and bound its cumulative regret in terms of maximal information gain, establishing a novel connection between GP optimization and experimental design. Moreover, by bounding the latter in terms of operator spectra, we obtain explicit sublinear regret bounds for many commonly used covariance functions.

The Best Deep Learning Papers from the ICLR 2020 Conference

In some important cases, our bounds have surprisingly weak dependence on the dimensionality. This paper has had profound impact over the past ten years, including the method itself, the proof techniques used, and the practical results. When nominating papers for this award, members of the award committee had the following to say about this paper:. The theorems and lemmas of this paper are quoted in recent papers, and their proof technique is borrowed in follow-up papers.

On the duo of technical depth and impact this paper clearly stands out. Hence, it has become a well-known paper, which has had influence both in theory and practice, due to the ongoing practical impact of Bayesian Optimization for experimental design, hyperparameter tuning and more.

However, there was no explicit finite sample convergence theory for this method. This leads to a first finite sample theoretical analysis for Bayesian optimization The award recipients were selected from a pool of papers nominated by Meta Reviewers by the Paper Awards committee:. Toggle navigation Toggle navigation Login. Year Test of Time Award The test of time award is given to a paper from ICML ten years ago that has had substantial impact on the field of machine learning, including both research and practice.

The following awards were announced at the presentation of the Test of Time award during the conference. Do not remove: This comment is monitored to verify that the site is working properly.Last week I had a pleasure to participate in the International Conference on Learning Representations ICLRan event dedicated to the research on all aspects of deep learning. Initially, the conference was supposed to take place in Addis Ababa, Ethiopia, however, due to the novel coronavirus pandemic, it went virtual.

iclr 2020 best paper award

Over speakers and attendees proved that the virtual format was more accessible for the public, but at the same time, the conference remained interactive and engaging. From many interesting presentations, I decided to choose 16which are influential and thought-provoking. Here are the best deep learning papers from the ICLR. Use it as a building block for more robust networks.

The architecture of an ODENet. The neural ODE block serves as a dimension-preserving nonlinear mapping. LinkedIn Website.

ICLR Deep Learning Conference - Best Paper Award

Paper Code. The colorbar indicates the number of iterations during training. New, general framework of target-embedding autoencoders or TEA for supervised prediction. Authors give both theoretical and empirical considerations. Solid lines correspond to the primary prediction task; dashed lines to the auxiliary reconstruction task. Shared components are involved in both. LinkedIn GitHub. 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.

The best achievable accuracy across retraining times by one-shot pruning. Neural nets, while capable of approximating complex functions, are rather poor in exact arithmetic operations.

This task was a longstanding challenge to deep learning researchers. Visualization of the NMU, where the weights W i,j controls gating between 1 identity or x ieach intermediate result is then multiplied explicitly to form z j.

Twitter LinkedIn GitHub. Each model on the training trajectory, shown as a point, is represented by its test predictions embedded into a two-dimensional space using UMAP. Example programs that illustrate limitations of existing approaches inculding both rulebased static analyzers and neural-based bug predictors.

We can significantly improve the computational efficiency of data selection in deep learning by using a much smaller proxy model to perform data selection. SVP applied to active learning left and core-set selection right. 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.

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. In both cases, we found the proxy and target model have high rank-order correlation, leading to similar selections and downstream results.Toggle navigation.

In addition, many accepted papers at the conference were contributed by our sponors.

IEEE ICC 2020 Best Paper Awards

The International Conference on Learning Representations ICLR is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.

ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics. Participants at ICLR span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

A non-exhaustive list of relevant topics explored at the conference include:. Toggle navigation Toggle navigation Login. Year About Us The International Conference on Learning Representations ICLR is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning. A non-exhaustive list of relevant topics explored at the conference include: unsupervised, semi-supervised, and supervised representation learning representation learning for planning and reinforcement learning representation learning for computer vision and natural language processing metric learning and kernel learning sparse coding and dimensionality expansion hierarchical models optimization for representation learning learning representations of outputs or states implementation issues, parallelization, software platforms, hardware applications in audio, speech, robotics, neuroscience, computational biology, or any other field societal considerations of representation learning including fairness, safety, privacy.

Do not remove: This comment is monitored to verify that the site is working properly.Visited local museums but did not book any extra activities (whale watching, guided tours) as we prefer to explore on our own. We had an amazing trip. It was so well curated. All of the destinations were thoughtful both in terms of location and distance traveled during the day. The sightseeing suggestions in the tour guide were excellent. The hotels and guest houses were all wonderful - comfortable and full of character.

To put together a trip like this on our own would have required weeks of online research and we never would have been able to achieve something this perfect. Thank you so much for a great trip.

iclr 2020 best paper award

My only question is: Why is there not an "Excellent" option. Our holiday was most excellent in every way.

ICCV19: Oral Session 1.1 - Award Papers

From my first email enquiry regarding the tour to the last minute of our holiday every aspect was excellent. Cecilia made the whole planning experience smooth and seamless, and the tour itself was most excellent. What an incredible job Nordic Visitor does. We felt so spoilt because everything had been done for us.

This was an incredible tour and I can't speak highly enough about the slick operation Nordic Visitor runs. It was a wonderful tour through the stunning scenery of Norway, very well organized by Nordic Visitor. Already thinking of visiting the northern part of Norway (Nordkapp, Lofoten) at some stage in the future, if a self-drive option is available.

Petra was very quick to answer any questions I had before I left the US. The accommodations were great and I would stay in the same hotels again.

ICLR 2020 | Virtual Conference Openly Available Online; No Best Paper Awards This Year

Service was exceptional and the rooms great. Breakfast at the hotels had great variety. I am so happy to have beautiful memories of Norway. She put our trip together perfectly and our entire visit from one country to the next was seamless. It could not have been any easier or well coordinated.

My emails were responded to promptly and all my questions were answered thoroughly and with patience. I usually plan all my trips myself but it was so nice to let Irja know what I wanted and let her do all the tedious planning and booking.

It was really amazing and our trip completely lived up to our expectations. I feel like a spoiled traveler now because Irja took a lot of the travel planning headache away from me and she did a really great job. We really appreciated the complimentary upgrades too. Just wanted to say we had a really lovely time on our 'grand tour' of the Highlands and Islands. We hadn't realised how many mountains Scotland had.How Does The Betting Expert Works.

The Betting Expert works on the stronger betting strategies figure out the profitable sports and to bets on. This program provides you the three steps on how to get the tips and earn on betting.

What Will You Get From The Betting Expert. It provides you the 60-day money back guarantee. In case, unfortunately for any reason, whether you are unable to get huge returns with this tipster, then you can able to get back your refund membership.

Whether you care about your economic, then you have to join this Betting Expert right now. This program has given a chance for 50 new members to the circle in very less time. Step One: Tips: The first thing is that you have to sign up with your right email id and password in this Betting Expert. By signing up to this program, you will get daily tips. So that this tipster will send you race tips every morning while also instructing you on how you have to bet.

Step Two: Bet: And then, you have to place your bets exactly and earn shedloads of money every day. You can also place the bet at any of your local bookies. Here, you will become the great part of the community of winners. Step Three: Win: Finally, you can start to see the substantial profits within 24 hours from right now. Here, you can begin betting like the shrewd investor without any constant losses.

The Betting Expert will help you to make more money from home without any experience or knowledge. You can easily begin making more cash with just single clicks on your computer. This method is completely easy that the picks are almost winners each time.

You will learn how to make huge financial returns from tiny deposits. Gareth Clark has developed this program based on his knowledge of betting, algorithms, statistics, mathematics, and data patterns. You will get the logical and profitable tipster tool to make more profits. Pros: The Betting Expert is the most trusted and easy to use betting tipster service. This program gives you with the betting edge, finding the best odds, collating data, and get profitable tips. Here, you will get the useful tips and betting strategies to help you to achieve the profitable bettor.

This tipster will help both the newbies and experienced bettors. This tipster program provides you the subscription fee in a matter of hours.

iclr 2020 best paper award

This program is user-friendly and highly reliable. Cons: The Betting Expert is available in Online only. Without the internet connection, you may not be able to get access to this tipster. Whether you are searching for quick money fix, then this Betting Expert is Not for you.

Tweet Share Pin it Comment Today Theme by WPExplorer Powered by WordPress. Download Betting Expert APK Latest VersionApp Rating: 4. This apk is safe to downloadCheck Previous VersionsOverall rating of apk of Betting Expert is 4. Please note that these are cumulative ratings since the app was listed on google play store.

Total number of reviews 41. Total number of five star reviews received: 22. This app has been rated 1 star(bad) by 4 number of users.


Bookmark the permalink.

Responses to Iclr 2020 best paper award

Leave a Reply

Your email address will not be published. Required fields are marked *