---
title: "NeurIPS 2016 — all accepted papers, page 2 — the most cited first"
description: "All 177 papers of NeurIPS 2016 · page 2 of 2, the most cited first; those with our summary link to it."
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# NeurIPS 2016: all accepted papers

177 papers · page 2 of 2 · the most cited first · [← NeurIPS 2016](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2016/)

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101. **[Unified Methods for Exploiting Piecewise Linear Structure in Convex Optimization ↗](https://papers.nips.cc/paper/6043-unified-methods-for-exploiting-piecewise-linear-structure-in-convex-optimization.pdf)**Tyler B. Johnon, Carlos Guestrin*11 citations*
102. **[A Probabilistic Model of Social Decision Making based on Reward Maximization ↗](https://papers.nips.cc/paper/6537-a-probabilistic-model-of-social-decision-making-based-on-reward-maximization.pdf)**Koosha Khalvati, Seongmin A. Park, Jean‐Claude Dreher et al.*10 citations*
103. **[A Probabilistic Programming Approach To Probabilistic Data Analysis ↗](https://papers.nips.cc/paper/2016/file/46072631582fc240dd2674a7d063b040-Paper.pdf)**Feras A. Saad, Vikash K. Mansinghka*10 citations*
104. **[Adversarial Multiclass Classification: A Risk Minimization Perspective ↗](https://papers.nips.cc/paper/2016/file/ad13a2a07ca4b7642959dc0c4c740ab6-Paper.pdf)**Rizal Fathony, Anqi Liu, Kaiser Asif et al.*10 citations*
105. **[Estimating Nonlinear Neural Response Functions using GP Priors and Kronecker Methods ↗](https://papers.nips.cc/paper/6153-estimating-nonlinear-neural-response-functions-using-gp-priors-and-kronecker-methods.pdf)**Cristina Savin, Gašper Tkačik*10 citations*
106. **[Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the Brain ↗](https://papers.nips.cc/paper/6274-generalized-correspondence-lda-models-gc-lda-for-identifying-functional-regions-in-the-brain.pdf)**Timothy N. Rubin, Sanmi Koyejo, Michael N. Jones et al.*10 citations*
107. **[Kernel observers: systems-theoretic modeling and inference of spatiotemporally evolving processes ↗](https://papers.nips.cc/paper/6189-kernel-observers-systems-theoretic-modeling-and-inference-of-spatiotemporally-evolving-processes.pdf)**Hassan A. Kingravi, Harshal Maske, Girish Vinayak Chowdhary*10 citations*
108. **[Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning ↗](https://papers.nips.cc/paper/6419-minimax-optimal-alternating-minimization-for-kernel-nonparametric-tensor-learning.pdf)**Taiji Suzuki, Heishiro Kanagawa, Hayato Kobayashi et al.*10 citations*
109. **[On Mixtures of Markov Chains ↗](https://papers.nips.cc/paper/6078-on-mixtures-of-markov-chains.pdf)**Rishi Gupta, Ravi Kumar, Sergei Vassilvitskii*10 citations*
110. **[Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics ↗](https://papers.nips.cc/paper/6077-online-bayesian-moment-matching-for-topic-modeling-with-unknown-number-of-topics.pdf)**Wei-Shou Hsu, Pascal Poupart*10 citations*
111. **[Scaled Least Squares Estimator for GLMs in Large-Scale Problems ↗](https://papers.nips.cc/paper/2016/file/e1696007be4eefb81b1a1d39ce48681b-Paper.pdf)**Murat A. Erdogdu, Lee H. Dicker, Mohsen Bayati*10 citations*
112. **[Algorithms and matching lower bounds for approximately-convex optimization ↗](https://papers.nips.cc/paper/6576-algorithms-and-matching-lower-bounds-for-approximately-convex-optimization.pdf)**Yuanzhi Li, Andrej Risteski*9 citations*
113. **[Brains on Beats ↗](https://papers.nips.cc/paper/6222-brains-on-beats.pdf)**Umut Güçlü, Jordy Thielen, Michael Hanke et al.*9 citations*
114. **[Clustering with Bregman Divergences: an Asymptotic Analysis ↗](https://papers.nips.cc/paper/6550-clustering-with-bregman-divergences-an-asymptotic-analysis.pdf)**Chaoyue Liu, Mikhail Belkin*9 citations*
115. **[Computing and maximizing influence in linear threshold and triggering models ↗](https://papers.nips.cc/paper/6347-computing-and-maximizing-influence-in-linear-threshold-and-triggering-models.pdf)**Justin Khim, Varun Jog, Po‐Ling Loh*9 citations*
116. **[Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions ↗](https://papers.nips.cc/paper/6337-dueling-bandits-beyond-condorcet-winners-to-general-tournament-solutions.pdf)**Siddartha Y. Ramamohan, Arun Rajkumar, Shivani Agarwal*9 citations*
117. **[Eliciting Categorical Data for Optimal Aggregation ↗](https://papers.nips.cc/paper/6237-eliciting-categorical-data-for-optimal-aggregation.pdf)**Chien-Ju Ho, Rafael Frongillo, Yiling Chen*9 citations*
118. **[Linear feature encoding for reinforcement learning ↗](https://papers.nips.cc/paper/6305-linear-feature-encoding-for-reinforcement-learning.pdf)**Zhao Song, Ronald Parr, Xuejun Liao et al.*9 citations*
119. **[Select-and-Sample for Spike-and-Slab Sparse Coding ↗](https://papers.nips.cc/paper/2016/file/de03beffeed9da5f3639a621bcab5dd4-Paper.pdf)**Abdul-Saboor Sheikh, Jörg Lücke*9 citations*
120. **[Bi-Objective Online Matching and Submodular Allocations ↗](https://papers.nips.cc/paper/6085-bi-objective-online-matching-and-submodular-allocations.pdf)**Hossein Esfandiari, Nitish Korula, Vahab Mirrokni*8 citations*
121. **[Efficient Neural Codes under Metabolic Constraints ↗](https://papers.nips.cc/paper/2016/file/e6c2dc3dee4a51dcec3a876aa2339a78-Paper.pdf)**Zhuo Wang, Xue-Xin Wei, Alan A. Stocker et al.*8 citations*
122. **[The Forget-me-not Process ↗](http://papers.nips.cc/paper/6055-the-forget-me-not-process.pdf)**Kieran Milan, Joel Veness, James E. Kirkpatrick et al.*8 citations*
123. **[Top-Down and Bottom-Up Interactions between Low-Level Reactive Control and Symbolic Rule Learning in Embodied Agents. ↗](http://ceur-ws.org/Vol-1773/CoCoNIPS_2016_paper8.pdf)**Clément Moulin-Frier, Xerxes D. Arsiwalla, Jordi-Ysard Puigbò et al.*8 citations*
124. **[Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making ↗](https://papers.nips.cc/paper/2016/file/97d0145823aeb8ed80617be62e08bdcc-Paper.pdf)**Himabindu Lakkaraju, Jure Leskovec*7 citations*
125. **[Identification and Overidentification of Linear Structural Equation Models ↗](https://papers.nips.cc/paper/2016/file/49c9adb18e44be0711a94e827042f630-Paper.pdf)**Bryant Chen*7 citations*
126. **[Off-policy experience retention for deep actor-critic learning ↗](https://research.tudelft.nl/en/publications/off-policy-experience-retention-for-deep-actor-critic-learning)**Tim de Bruin, Jens Kober, Karl Tuyls et al.*7 citations*
127. **[On the Recursive Teaching Dimension of VC Classes ↗](https://papers.nips.cc/paper/2016/file/69a5b5995110b36a9a347898d97a610e-Paper.pdf)**Xi Chen, Yu Cheng, Bo Tang*7 citations*
128. **[The Limits of Learning with Missing Data ↗](https://papers.nips.cc/paper/6171-the-limits-of-learning-with-missing-data.pdf)**Brian Bullins, Elad Hazan, Tomer Koren*7 citations*
129. **[A Bandit Framework for Strategic Regression ↗](https://proceedings.neurips.cc/paper/2016/file/d79aac075930c83c2f1e369a511148fe-Paper.pdf)**Liu Yang, Yiling Chen*6 citations*
130. **[Even Faster SVD Decomposition Yet Without Agonizing Pain ↗](http://papers.nips.cc/paper/6507-even-faster-svd-decomposition-yet-without-agonizing-pain.pdf)**Zeyuan Allen-Zhu, Yuanzhi Li*6 citations*
131. **[Exploiting tradeoffs for exact recovery in heterogeneous stochastic block models ↗](https://papers.nips.cc/paper/6574-exploiting-tradeoffs-for-exact-recovery-in-heterogeneous-stochastic-block-models.pdf)**Amin Jalali, Qiyang Han, Ioana Dumitriu et al.*6 citations*
132. **[Feature-distributed sparse regression: a screen-and-clean approach ↗](https://papers.nips.cc/paper/6187-feature-distributed-sparse-regression-a-screen-and-clean-approach.pdf)**Jiyan Yang, Michael W. Mahoney, Michael A. Saunders et al.*6 citations*
133. **[Learning Parametric Sparse Models for Image Super-Resolution ↗](https://papers.nips.cc/paper/2016/file/619205da514e83f869515c782a328d3c-Paper.pdf)**Yongbo Li, Weisheng Dong, Xuemei Xie et al.*6 citations*
134. **[Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games ↗](https://papers.nips.cc/paper/6216-minimizing-regret-on-reflexive-banach-spaces-and-nash-equilibria-in-continuous-zero-sum-games.pdf)**Maximilian Balandat, Walid Krichene, Claire Jennifer Tomlin et al.*6 citations*
135. **[Optimal Sparse Linear Encoders and Sparse PCA ↗](http://papers.nips.cc/paper/6252-optimal-sparse-linear-encoders-and-sparse-pca.pdf)**Malik Magdon‐Ismail, Christos Boutsidis*6 citations*
136. **[A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics ↗](https://papers.nips.cc/paper/2016/file/062ddb6c727310e76b6200b7c71f63b5-Paper.pdf)**William Hoiles, Mihaela van der Schaar*5 citations*
137. **[Active Learning with Oracle Epiphany ↗](https://papers.nips.cc/paper/6155-active-learning-with-oracle-epiphany.pdf)**Tzu-Kuo Huang, Lihong Li, Ara Vartanian et al.*5 citations*
138. **[Efficient and robust spiking neural circuit for navigation inspired by echolocating bats ↗](https://papers.nips.cc/paper/6558-efficient-and-robust-spiking-neural-circuit-for-navigation-inspired-by-echolocating-bats.pdf)**Pulkit Tandon, Yash H. Malviya, Bipin Rajendran*5 citations*
139. **[Graph Clustering: Block-models and model free results ↗](https://papers.nips.cc/paper/2016/file/286674e3082feb7e5afb92777e48821f-Paper.pdf)**Yali Wan, Marina Meilă*5 citations*
140. **[Graphical Time Warping for Joint Alignment of Multiple Curves ↗](https://papers.nips.cc/paper/2016/file/f0bbac6fa079f1e00b2c14c1d3c6ccf0-Paper.pdf)**Yizhi Wang, David Jonathan Miller, Kira E. Poskanzer et al.*5 citations*
141. **[Error analysis of generalized nyström kernel regression ↗](https://papers.nips.cc/paper/6602-error-analysis-of-generalized-nystrom-kernel-regression.pdf)**Hong Chen, Haifeng Xia, Heng Huang et al.*4 citations*
142. **[Improved Error Bounds for Tree Representations of Metric Spaces ↗](https://papers.nips.cc/paper/6431-improved-error-bounds-for-tree-representations-of-metric-spaces.pdf)**Samir Chowdhury, Facundo Mémoli, Zane Smith*4 citations*
143. **[Learned Region Sparsity and Diversity Also Predicts Visual Attention ↗](https://papers.nips.cc/paper/6451-learned-region-sparsity-and-diversity-also-predicts-visual-attention.pdf)**Zijun Wei, Hossein Adeli, Minh Hoai Nguyen et al.*4 citations*
144. **[Near-Optimal Smoothing of Structured Conditional Probability Matrices ↗](https://papers.nips.cc/paper/2016/file/8bdb5058376143fa358981954e7626b8-Paper.pdf)**Moein Falahatgar, Mesrob I. Ohannessian, Alon Orlitsky*4 citations*
145. **[{A central limit theorem with application to inference in α-stable regression models} ↗](http://proceedings.mlr.press/v55/riabiz16.pdf)**Marina Riabiz, Tohid Ardeshiri, Simon Godsill*4 citations*
146. **[Blind attacks on machine learners ↗](https://papers.nips.cc/paper/2016/file/a284df1155ec3e67286080500df36a9a-Paper.pdf)**Alex Beatson, Zhaoran Wang, Han Liu*3 citations*
147. **[Crossmodal Language Grounding, Learning, and Teaching. ↗](http://ceur-ws.org/Vol-1773/CoCoNIPS_2016_paper5.pdf)**Stefan Heinrich, Cornelius Weber, Stefan Wermter et al.*3 citations*
148. **[Inverted HMM - a Proof of Concept ↗](http://publications.rwth-aachen.de/record/686519)**Patrick Doetsch, Hermann Ney, Stefan Hegselmann et al.*3 citations*
149. **[Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics ↗](https://papers.nips.cc/paper/6582-neurons-equipped-with-intrinsic-plasticity-learn-stimulus-intensity-statistics.pdf)**Travis Monk, Cristina Savin, Jörg Lücke*3 citations*
150. **[Unsupervised Learning from Noisy Networks with Applications to Hi-C Data ↗](https://papers.nips.cc/paper/6291-unsupervised-learning-from-noisy-networks-with-applications-to-hi-c-data.pdf)**Bo Wang, Junjie Zhu, Armin Pourshafeie et al.*3 citations*
151. **[ANALOGY-BASED REASONING WITH MEMORY NETWORKS FOR FUTURE PREDICTION ↗](http://ceur-ws.org/Vol-1773/CoCoNIPS_2016_paper3.pdf)**Daniel Andrade, Bing Bai, Ramkumar Rajendran et al.*2 citations*
152. **[Probabilistic Inference with Generating Functions for Poisson Latent Variable Models ↗](https://papers.nips.cc/paper/2016/file/6c1da886822c67822bcf3679d04369fa-Paper.pdf)**Kevin Winner, Daniel R. Sheldon*2 citations*
153. **[Variational Bayes on Monte Carlo Steroids ↗](https://papers.nips.cc/paper/6259-variational-bayes-on-monte-carlo-steroids.pdf)**Aditya Grover, Stefano Ermon*2 citations*
154. **[An algorithm for L1 nearest neighbor search via monotonic embedding ↗](http://papers.nips.cc/paper/6227-an-algorithm-for-l1-nearest-neighbor-search-via-monotonic-embedding.pdf)**Xin’an Wang, Sanjoy Dasgupta*1 citation*
155. **[Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods ↗](https://papers.nips.cc/paper/6169-approximate-maximum-entropy-principles-via-goemans-williamson-with-applications-to-provable-variational-methods.pdf)**Andrej Risteski, Yuanzhi Li*1 citation*
156. **[Convex Two-Layer Modeling with Latent Structure ↗](https://papers.nips.cc/paper/6314-convex-two-layer-modeling-with-latent-structure.pdf)**Vignesh Ganapathiraman, Xinhua Zhang, Yaoliang Yu et al.*1 citation*
157. **[Cooperative Graphical Models ↗](https://papers.nips.cc/paper/6122-cooperative-graphical-models.pdf)**Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek et al.*1 citation*
158. **[Dropout-based Automatic Relevance Determination ↗](https://istina.msu.ru/publications/article/40114782/)**Dmitry Mikhaylov, A. Arseniy, Гнатышак Дмитрий Вадимович*1 citation*
159. **[ELFI: Engine for Likelihood-Free Inference ↗](https://research.aalto.fi/en/publications/elfi-engine-for-likelihood-free-inference)**Antti Kangasrääsiö, Jarno Lintusaari, Kusti Skytén et al.*1 citation*
160. **[Learning User Perceived Clusters with Feature-Level Supervision ↗](https://papers.nips.cc/paper/6260-learning-user-perceived-clusters-with-feature-level-supervision.pdf)**Ting-Yu Cheng, Guiguan Lin, xinyang gong et al.*1 citation*
161. **[Learning analytics: Collaborative filtering or regression with experts? ↗](https://koasas.kaist.ac.kr/handle/10203/214702)**Kangwook Lee, Changho Suh, Jichan Chung et al.*1 citation*
162. **[Learning under uncertainty: a comparison between R-W and Bayesian approach ↗](https://papers.nips.cc/paper/2016/file/14d9e8007c9b41f57891c48e07c23f57-Paper.pdf)**He Huang, Martin P. Paulus*1 citation*
163. **[Multi-step learning and underlying structure in statistical models ↗](https://papers.nips.cc/paper/6197-multi-step-learning-and-underlying-structure-in-statistical-models.pdf)**Maia Fraser*1 citation*
164. **[Neuro-Symbolic EDA-Based Optimization Using ILP-Enhanced DBNs. ↗](http://ceur-ws.org/Vol-1773/CoCoNIPS_2016_paper7.pdf)**Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan et al.*1 citation*
165. **[Regret Bounds for Non-decomposable Metrics with Missing Labels ↗](https://papers.nips.cc/paper/2016/file/2dffbc474aa176b6dc957938c15d0c8b-Paper.pdf)**Nagarajan Natarajan, Prateek Jain*1 citation*
166. **[Variable Binding through Assemblies in Spiking Neural Networks. ↗](http://ceur-ws.org/Vol-1773/CoCoNIPS_2016_paper1.pdf)**Robert A. Legenstein, Christos H. Papadimitriou, Santosh Vempala et al.*1 citation*
167. **[A posteriori error bounds for joint matrix decomposition problems ↗](https://papers.nips.cc/paper/6424-a-posteriori-error-bounds-for-joint-matrix-decomposition-problems.pdf)**Nicolò Colombo, Nikos A. Vlassis
168. **[Combining Low-Density Separators with CNNs ↗](https://papers.nips.cc/paper/6408-combining-low-density-separators-with-cnns)**Yu-Xiong Wang, Martial Hebert
169. **[Constraints Based Convex Belief Propagation ↗](https://papers.nips.cc/paper/6219-constraints-based-convex-belief-propagation.pdf)**Yaniv Tenzer, Alexander Gerhard Schwing, Kevin Gimpel et al.
170. **[Information-Theoretic Bounded Rationality for Learning and Decision-Making ↗](https://pure.mpg.de/pubman/faces/ViewItemOverviewPage.jsp?itemId=item_2547381)**Daniel A. Braun
171. **[Learning Additive Exponential Family Graphical Models via 2,1-norm Regularized M-Estimation ↗](https://papers.nips.cc/paper/6106-learning-additive-exponential-family-graphical-models-via-ell_21-norm-regularized-m-estimation.pdf)**Xiao–Tong Yuan, Ping Li, Tong Zhang et al.
172. **[Learning to predict: A fast re-constructive method to generate multimodal embeddings ↗](https://lirias.kuleuven.be/bitstream/123456789/556185/4/NIPS2016.pdf)**Guillem Collell, Teddy Zhang, Marie‐Francine Moens
173. **[Re-using gradient computation in automatic variational inference ↗](https://researchportal.helsinki.fi/en/publications/re-using-gradient-computation-in-automatic-variational-inference)**Joseph Sakaya, Arto Klami A
174. **[Resource-Efficient Feature Gathering at Test Time ↗](http://www.research.ed.ac.uk/portal/en/publications/resourceefficient-feature-gathering-at-test-time(e7e66a36-6b35-4340-aae3-d64cd6a3a114).html)**Gavin Douglas Buchanan Gray, Amos Storkey
175. **[The Product Cut ↗](https://papers.nips.cc/paper/6226-the-product-cut.pdf)**Thomas Laurent, James H. von Brecht, Xavier Bresson et al.
176. **[Towards Never-Ending Learning From Parallel Time-Series ↗](http://www.inescporto.pt/~jsc/publications/conferences/2016SamanehNIPSTSW.pdf)**Samaneh Khoshrou, Jaime S. Cardoso
177. **[Ultra-High Resolution Functional BOLD Imaging: Do We Really See More? ↗](https://pure.mpg.de/pubman/faces/ViewItemOverviewPage.jsp?itemId=item_2547415)**Klaus Scheffler

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