丁香五月天婷婷久久婷婷色综合91|国产传媒自偷自拍|久久影院亚洲精品|国产欧美VA天堂国产美女自慰视屏|免费黄色av网站|婷婷丁香五月激情四射|日韩AV一区二区中文字幕在线观看|亚洲欧美日本性爱|日日噜噜噜夜夜噜噜噜|中文Av日韩一区二区

您正在使用IE低版瀏覽器,為了您的雷峰網(wǎng)賬號(hào)安全和更好的產(chǎn)品體驗(yàn),強(qiáng)烈建議使用更快更安全的瀏覽器
此為臨時(shí)鏈接,僅用于文章預(yù)覽,將在時(shí)失效
人工智能 正文
發(fā)私信給奕欣
發(fā)送

0

NIPS 2017錄用結(jié)果全公布,清華北大10篇,BAT 4篇(附詳細(xì)名單)

本文作者: 奕欣 2017-09-13 15:32 專題:NIPS 2017
導(dǎo)語:本屆NIPS共收到 3240 篇論文投稿,錄用 678 篇,錄用率為 20.9%;其中包括 40 篇口頭報(bào)告論文和 112 篇spotlight論文。

NIPS 2017錄用結(jié)果全公布,清華北大10篇,BAT 4篇(附詳細(xì)名單)

雷鋒網(wǎng)AI科技評(píng)論按:NIPS 2017 將于 12 月份在美國(guó)長(zhǎng)灘舉行,本屆NIPS共收到 3240 篇論文投稿,錄用 678 篇,錄用率為 20.9%;其中包括 40 篇口頭報(bào)告論文和 112 篇 spotlight 論文。詳細(xì)錄用名單日前已經(jīng)公布,可參見:https://nips.cc/Conferences/2017/AcceptedPapersInitial

為方便瀏覽全貌,雷鋒網(wǎng)AI科技評(píng)論為讀者整理了多家高校及企業(yè)的錄用名單。

先來看看國(guó)內(nèi)高校情況。國(guó)人心目中科研實(shí)力最強(qiáng)的清華大學(xué),今年共有6篇錄用論文,包括張鈸院士、王建民博士、魯繼文博士、朱軍博士都有論文被錄用;而北京大學(xué)也表現(xiàn)不俗,有四篇論文被錄用。此外,包括中國(guó)科學(xué)院、中國(guó)科學(xué)技術(shù)大學(xué)、香港科技大學(xué)、香港中文大學(xué)及香港城市大學(xué)在內(nèi)的多家高校也有多篇論文中了NIPS。由于論文可能涉及多位合作者,因此以下的名單均以第一作者所屬機(jī)構(gòu)為準(zhǔn)。

清華大學(xué)

  • PredRNN: Recurrent Neural Networks for Video Prediction using Spatiotemporal LSTMs

    Yunbo Wang (Tsinghua University) · Mingsheng Long (Tsinghua University) · Jianmin Wang (Tsinghua University) · Philip S Yu (UIC)

  • Learning Multiple Tasks with Deep Relationship Networks

    Mingsheng Long (Tsinghua University) · Jianmin Wang (Tsinghua University) · Philip S Yu (UIC)

  • Runtime Neural Pruning

    Ji Lin (Tsinghua University) · Yongming Rao (Tsinghua University) · Jiwen Lu (Tsinghua University)

  • Triple Generative Adversarial Nets

    Chongxuan LI (Tsinghua University) · Kun Xu () · Jun Zhu (Tsinghua University) · Bo Zhang (Tsinghua University)

  • Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex

    Chaobing Song (Tsinghua University) · Shaobo Cui (Tsinghua University) · Shu-Tao Xia (Tsinghua University) · Yong Jiang (Tsinghua-Berkeley Shenzhen Institute)

  • Population Matching Discrepancy and Applications in Deep Learning

    Jianfei Chen (Tsinghua University) · Chongxuan LI (Tsinghua University) · Yizhong Ru (Tsinghua University) · Jun Zhu (Tsinghua University)

北京大學(xué)

  • Deep Dynamic Poisson Factorization Model

    Chengyue Gong (PeKing University) ? win-bin huang (peking university)

  • Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers

    Cong Fang (Peking University) · Feng Cheng (Peking University) · Zhouchen Lin (Peking University)

  • From Bayesian Sparsity to Gated Recurrent Nets

    Hao He (PekingUniversity) · Bo Xin (Microsoft Research) · David Wipf (Microsoft Research)

  • The Expressive Power of Neural Networks: A View from the Width

    Zhou Lu (Peking University) · Hongming Pu (Peking university) · Feicheng Wang (Peking University) · Zhiqiang Hu (Peking University) · Liwei Wang (Peking University)

中國(guó)科學(xué)院

  • Deep supervised discrete hashing

    Qi Li (Institute of Automation, Chinese Academy of Sciences) · Zhenan Sun () · Ran He (CASIA) · Tieniu Tan (Chinese Academy of Sciences)

中國(guó)科學(xué)技術(shù)大學(xué)

  • Deliberation Networks: Sequence Generation Beyond One-Pass Decoding

    Yingce Xia (University of Science and Technology of China) · Lijun Wu (Sun Yat-sen University) · Jianxin Lin (USTC) · Fei Tian (Miicrosoft Research) · Tao Qin (Microsoft Research) · Tie-Yan Liu (Microsoft Research)

  • Subset Selection under Noise

    Chao Qian (University of Science and Technology of China) · Jing-Cheng Shi (Nanjing University) · Yang Yu () · Ke Tang (University of Science and Technology of China) · Zhi-Hua Zhou (Nanjing University)

香港中文大學(xué)

  • Rethinking Feature Discrimination and Polymerization for Large-scale Recognition

    Yu Liu (The Chinese University of Hong Kong) · Hongyang Li (The Chinese University of Hong Kong) · Xiaogang Wang (The Chinese University of Hong Kong)

  • Contrastive Learning for Image Captioning

    Bo Dai (The Chinese University of Hong Kong) · Dahua Lin (The Chinese University of Hong Kong)

  • Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds

    Yuanyuan Liu (The Chinese University of Hong Kong) · Fanhua Shang (The Chinese University of Hong Kong) · James Cheng (The Chinese University of Hong Kong) · Hong Cheng (The Chinese University of Hong Kong) · Licheng Jiao (Xidian University)

  • Geometric Descent Method for Convex Composite Minimization

    Shixiang Chen (The Chinese University of HongKong) · Shiqian Ma (UC Davis) · Wei Liu (Tencent Technology (Shenzhen) Company Limited)

香港城市大學(xué)

  • Incorporating Side Information by Adaptive Convolution

    Di Kang (City University of Hong Kong) · Debarun Dhar (City University of Hong Kong) · Antoni Chan (City University of Hong Kong)

香港科技大學(xué)

  • Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model

    Xingjian Shi (HKUST) · Hao Wang (HKUST) · Zhihan Gao (HKUST) · Leonard Lausen (HKUST) · Dit-Yan Yeung (HKUST, Hong Kong) · Wang-chun WOO (HKO) · Wai-kin Wong (HKO)

自 1987 年到 2000 年,NIPS都在美國(guó)丹佛舉辦,雖然后來也曾經(jīng)在加拿大溫哥華、西班牙的格蘭納達(dá)、加拿大蒙特利爾舉辦,但不得不承認(rèn)的是,美國(guó)一直是全球科研的主要陣地。今年NIPS上,美國(guó)計(jì)算機(jī)四大名校(CMU、MIT、UC伯克利、斯坦福)“理所當(dāng)然”地霸屏,僅以第一作者所屬機(jī)構(gòu)統(tǒng)計(jì)的錄用論文就達(dá)92篇(有一篇是第一作者隸屬雙院校的),其中 CMU 37篇,成為今年最大贏家;MIT和斯坦福各有20篇論文,UC伯克利有16篇論文被錄用。

由于正文篇幅有限,關(guān)注“AI科技評(píng)論”(aitechtalk)后,回復(fù)“美國(guó)名校NIPS”可查看四大名校論文完整名單。

再和雷鋒網(wǎng)AI科技評(píng)論一起來看看國(guó)內(nèi)BAT三家的論文錄用情況。今年NIPS上,尚未看到阿里被錄用的論文,騰訊有一篇作為第一作者的錄用論文,另有兩篇為合作論文;而百度美研院今年有一篇關(guān)于Deep Voice2的論文被收錄;截至目前,尚未看到阿里的相關(guān)錄用論文。

騰訊

  • Mixture-Rank Matrix Approximation for Collaborative Filtering

    Dongsheng Li (IBM Research - China) · Chao Chen (Tongji University) · Wei Liu (Tencent Technology (Shenzhen) Company Limited) · Tun Lu (Fudan University) · Ning Gu (Fudan University) · Stephen Chu (IBM Research - China)

  • Geometric Descent Method for Convex Composite Minimization

    Shixiang Chen (The Chinese University of HongKong) · Shiqian Ma (UC Davis) · Wei Liu (Tencent Technology (Shenzhen) Company Limited)

  • Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding

    Wenbing Huang (Tencent AI Lab) · Fuchun Sun (Tsinghua University) · Tong Zhang (The Australian National University) · Junzhou Huang (University of Texas at Arlington) · Mehrtash Harandi (Data61)

百度研究院

  • Deep Voice 2: Multi-Speaker Neural Text-to-Speech

    Andrew Gibiansky (Baidu Research)

最后再看看其它國(guó)際研究院/企業(yè)的表現(xiàn)。驚喜之外意料之中的是,微軟研究院共有16篇第一作者論文被錄用,包括此前雷鋒網(wǎng)AI科技評(píng)論報(bào)道提及的,微軟亞洲研究院的4篇文章。谷歌今年有7篇論文上榜,OpenAI,F(xiàn)acebook也表現(xiàn)不俗。

往期報(bào)道可參閱:http://www.ozgbdpf.cn/news/201709/BiZ4ytOqR0LOHZnN.html

微軟研究院

  • Decoding with Value Networks for Neural Machine Translation

    Di He (Microsoft Research) · Hanqing Lu (Zhejiang University) · Yingce Xia (University of Science and Technology of China) · Tao Qin (Microsoft Research) · Liwei Wang (Peking University) · Tieyan Liu (Microsoft Research)

  • Inference in Graphical Models via Semidefinite Programming Hierarchies

    Murat Erdogdu (Microsoft Research) · Yash Deshpande (MIT) · Andrea Montanari (Stanford)

  • Neural Program Meta-Induction

    Jacob Devlin (Microsoft Research) · Rudy R Bunel (Oxford University) · Rishabh Singh (Microsoft Research) · Matthew Hausknecht (Microsoft Research) · Pushmeet Kohli (DeepMind)

  • Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM

    Steven Wu (Microsoft Research) · Bo Waggoner () · Seth Neel (University of Pennsylvania) · Aaron Roth (University of Pennsylvania) · Katrina Ligett ()

  • A Highly Efficient Gradient Boosting Decision Tree

    Guolin Ke (Microsoft Research) · Qi Meng (Peking University) · Taifeng Wang (Microsoft Research) · Wei Chen (Microsoft Research Asia) · Weidong Ma (Microsoft Research) · Tie-Yan Liu (Microsoft Research)

  • Clustering Billions of Reads for DNA Data Storage

    Cyrus Rashtchian (University of Washington) · Konstantin Makarychev (Microsoft) · Luis Ceze (Microsoft) · Karin Strauss (Microsoft Research) · Sergey Yekhanin (Microsoft) · Djordje Jevdjic (Microsoft Research) · Miklos Racz (Princeton University) · Siena Ang (Microsoft)

  • Collecting Telemetry Data Privately

    Bolin Ding (Microsoft) · Janardhan Kulkarni (Microsoft Research) · Sergey Yekhanin (Microsoft)

  • Off-policy evaluation for slate recommendation

    Adith Swaminathan (Microsoft Research) · Akshay Krishnamurthy () · Alekh Agarwal (Microsoft Research) · Miro Dudik (Microsoft Research) · John Langford (Microsoft Research) · Damien Jose (Microsoft) · Imed Zitouni (Microsoft)

  • A Decomposition of Forecast Error in Prediction Markets

    Miro Dudik (Microsoft Research) · Sebastien Lahaie (Google) · Ryan M Rogers (University of Pennsylvania) · Jennifer Wortman Vaughan (Microsoft Research)

  • Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation

    Christian Borgs (Microsoft Research New England) · Jennifer Chayes (Microsoft Research) · Christina Lee (MIT) · Devavrat Shah (Massachusetts Institute of Technology)

  • Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes

    Jianshu Chen (Microsoft Research, Redmond, W) · Chong Wang () · Lin Xiao (Microsoft Research) · Ji He (University Washington) · Lihong Li (Microsoft Research) · Li Deng (Citadel)

  • Online Learning with a Hint

    Ofer Dekel (Microsoft Research) · arthur flajolet (MIT) · Nika Haghtalab (Carnegie Mellon University) · Patrick Jaillet (Massachusetts Institute of Technology)

  • A Sample Complexity Measure with Applications to Learning Optimal Auctions

    Vasilis Syrgkanis (Microsoft Research)

  • Hybrid Reward Architecture for Reinforcement Learning

    Harm Van Seijen (Microsoft Research) · Romain Laroche () · Mehdi Fatemi () · Joshua Romoff (McGill University)

  • Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls

    Zeyuan Allen-Zhu (Microsoft Research) · Elad Hazan (Princeton University) · Wei Hu (Princeton University) · Yuanzhi Li (Princeton University)

  • Z-Forcing: Training Stochastic Recurrent Networks

    Marc-Alexandre C?té (Microsoft Maluuba) · Alessandro Sordoni (Microsoft Maluuba) · Anirudh Goyal ALIAS PARTH GOYAL (Université de Montréal) · Nan Ke (MILA, école Polytechnique de Montréal) · Yoshua Bengio (U. Montreal)

谷歌

  • On the Consistency of Quick Shift

    Heinrich Jiang (Google)

  • Attention is All you Need

    Ashish Vaswani (Google Brain) · Noam Shazeer (Google) · Niki Parmar (Google) · Llion Jones (Google) · Jakob Uszkoreit (Google, Inc.) · Aidan N Gomez (University of Toronto) · ?ukasz Kaiser (Google Brain)

    雷鋒網(wǎng)AI科技評(píng)論往期報(bào)道:http://www.ozgbdpf.cn/news/201706/H2PUINRPl9XKrC1R.html

  • Parameter-Free Online Learning via Model Selection

    Dylan J Foster (Cornell University) · Satyen Kale (Google) · Mehryar Mohri (Courant Institute and Google) · Karthik Sridharan (Cornell University)

  • SVCCA: Singular Vector Canonical Correlation Analysis for Deep Understanding and Improvement

    Maithra Raghu (Cornell University and Google Brain) · Justin Gilmer (Google Brain) · Jason Yosinski (Uber) · Jascha Sohl-Dickstein (Google Brain)

  • Neural Discrete Representation Learning

    Aaron van den Oord (Google Deepmind) · Oriol Vinyals (Google DeepMind) · koray kavukcuoglu (DeepMind)

  • Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

    Balaji Lakshminarayanan (Google Deepmind) · Alexander Pritzel (Google Deepmind) · Charles Blundell (DeepMind)

  • Acceleration and Averaging in Stochastic Descent Dynamics

    Walid Krichene (Google)

OpenAI

  • Deep Reinforcement Learning from Human Preferences

    Paul F Christiano (OpenAI) · Jan Leike (DeepMind) · Tom Brown (OpenAI) · Miljan Martic (DeepMind) · Shane Legg (DeepMind) · Dario Amodei (OpenAI)

  • Hindsight Experience Replay

    Marcin Andrychowicz (OpenAI) · Filip Wolski (OpenAI) · Alex Ray (OpenAI) · Jonas Schneider (OpenAI) · Rachel Fong (OpenAI) · Peter Welinder (OpenAI) · Bob McGrew (OpenAI) · Josh Tobin (OpenAI) · OpenAI Pieter Abbeel (OpenAI, UC Berkeley) · Wojciech Zaremba (OpenAI)

  • Hierarchical Implicit Models and Likelihood-Free Variational Inference

    Dustin Tran (Columbia University & OpenAI) · Rajesh Ranganath (Princeton University) · David Blei (Columbia University)

Facebook

  • ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games

    Yuandong Tian (Facebook AI Research) · Qucheng Gong (Facebook AI Research) · Wenling Shang (435024885627) · Yuxin Wu (Facebook AI Research) · C. Lawrence Zitnick (Facebook AI Research)

    雷鋒網(wǎng)AI科技評(píng)論往期報(bào)道:http://www.ozgbdpf.cn/news/201709/aZ33T276udayVdjz.html

  • Multi-agent Predictive Modeling with Attentional CommNets

    Yedid Hoshen (Facebook AI Research)

  • Fader Networks: Generating Image Variations by Sliding Attribute Values

    Guillaume Lample (Facebook AI Research) · Neil Zeghidour (Facebook A.I. Research / Ecole Normale Supérieure) · Nicolas Usunier (Facebook AI Research) · Antoine Bordes (Facebook AI Research) · Ludovic DENOYER (Universite Pierre et Marie Curie - Paris) · Marc'Aurelio Ranzato (Facebook)

  • Poincaré Embeddings for Learning Hierarchical Representations

    Maximillian Nickel (Facebook) · Douwe Kiela (Facebook AI Research)

  • Gradient Episodic Memory for Continuum Learning

    David Lopez-Paz (Facebook AI Research) · Marc'Aurelio Ranzato (Facebook)

  • Houdini: Democratizing Adversarial Examples

    Moustapha Cisse (Facebook AI Research) · Yossi Adi (Bar Ilan University) · Natalia Neverova (Facebook AI Research) · Joseph Keshet (Bar-Ilan University)

更多資訊敬請(qǐng)關(guān)注雷鋒網(wǎng)AI科技評(píng)論。

雷峰網(wǎng)原創(chuàng)文章,未經(jīng)授權(quán)禁止轉(zhuǎn)載。詳情見轉(zhuǎn)載須知。

NIPS 2017錄用結(jié)果全公布,清華北大10篇,BAT 4篇(附詳細(xì)名單)

分享:
相關(guān)文章
當(dāng)月熱門文章
最新文章
請(qǐng)?zhí)顚懮暾?qǐng)人資料
姓名
電話
郵箱
微信號(hào)
作品鏈接
個(gè)人簡(jiǎn)介
為了您的賬戶安全,請(qǐng)驗(yàn)證郵箱
您的郵箱還未驗(yàn)證,完成可獲20積分喲!
請(qǐng)驗(yàn)證您的郵箱
立即驗(yàn)證
完善賬號(hào)信息
您的賬號(hào)已經(jīng)綁定,現(xiàn)在您可以設(shè)置密碼以方便用郵箱登錄
立即設(shè)置 以后再說