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- Learning Supervised Binary Hashing without Binary Code Optimization (Miguel Carreira-Perpinan; Ramin Raziperchikolaei)
- Sub-linear Privacy-preserving Search with Unsecured Server and Semi-honest Parties (Beidi Chen)
- On Nearest Neighbors in Non Local Means Denoising (Iuri Frosio; Kautz Jan)
- Fast k-Nearest Neighbour Search via Prioritized DCI (Ke Li; Jitendra Malik)
- Generative Local Metric Learning for Nearest Neighbor Methods (Yung-Kyun Noh; Masashi Sugiyama; Daniel D Lee)
- Private Document Classification in Federated Databases (Phillipp Schoppmann; Adria Gascon; Borja Balle)
- Optimizing Revenue Over Data-Driven Assortments (Deeksha Sinha; Theja Tulabandula)
- Fast Distance Metric Learning for Multi-Task Large Margin Nearest Neighbor Classification (Adams Yu)
Author Information
Beidi Chen (Rice University)
I'm a third year Ph.D. Student at Rice University and working with Dr. Anshumali Shrivastava. My research topic is hashing in large-scale learning. I work closely with Dr. Rebecca Steorts on Record Linkage. I had my undergrad in Berkeley and my Advisor was Randy Katz. My topic was data mining.
Borja Balle (DeepMind)
Daniel Lee (Cornell Tech)
iuri frosio (nvidia)
Jitendra Malik (University of California at Berkley)
Jan Kautz (NVIDIA)
Ke Li (UC Berkeley)
Masashi Sugiyama (RIKEN / University of Tokyo)
Miguel A. Carreira-Perpinan (University of California, Merced)
Ramin Raziperchikolaei (UC Merced)
Theja Tulabandhula (University of Illinois Chicago)
Theja is a researcher working in the areas of reinforcement, online and deep machine learning with applications to transportation, retail and other fields. He received his combined bachelors and masters degree in electrical engineering with honors from Indian Institute of Technology, Kharagpur, in 2009. There, he was awarded the Prime Minister of India Gold medal for getting the highest GPA among all dual degree students. He received his Ph.D. degree in 2014, in electrical engineering and computer science at the Massachusetts Institute of Technology (MIT), Cambridge. There, he was a Xerox-MIT fellow and a Science and Technology Fulbright scholar. Please visit http://www.theja.org/ for more information!
Yung-Kyun Noh (Seoul National University)
Adams Wei Yu (Carnegie Mellon University)
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Sifei Liu · Shalini De Mello · Jinwei Gu · Guangyu Zhong · Ming-Hsuan Yang · Jan Kautz -
2017 Poster: Positive-Unlabeled Learning with Non-Negative Risk Estimator »
Ryuichi Kiryo · Gang Niu · Marthinus C du Plessis · Masashi Sugiyama -
2017 Poster: Learning from Complementary Labels »
Takashi Ishida · Gang Niu · Weihua Hu · Masashi Sugiyama -
2017 Oral: Positive-Unlabeled Learning with Non-Negative Risk Estimator »
Ryuichi Kiryo · Gang Niu · Marthinus C du Plessis · Masashi Sugiyama -
2017 Poster: Learning a Multi-View Stereo Machine »
Abhishek Kar · Christian Häne · Jitendra Malik -
2017 Poster: Hierarchical Methods of Moments »
Matteo Ruffini · Guillaume Rabusseau · Borja Balle -
2017 Poster: Expectation Propagation for t-Exponential Family Using q-Algebra »
Futoshi Futami · Issei Sato · Masashi Sugiyama -
2017 Poster: Generative Local Metric Learning for Kernel Regression »
Yung-Kyun Noh · Masashi Sugiyama · Kee-Eung Kim · Frank Park · Daniel Lee -
2017 Poster: Multitask Spectral Learning of Weighted Automata »
Guillaume Rabusseau · Borja Balle · Joelle Pineau -
2016 Workshop: Private Multi-Party Machine Learning »
Borja Balle · Aurélien Bellet · David Evans · Adrià Gascón -
2016 Poster: An ensemble diversity approach to supervised binary hashing »
Miguel A. Carreira-Perpinan · Ramin Raziperchikolaei -
2016 Poster: Optimizing affinity-based binary hashing using auxiliary coordinates »
Ramin Raziperchikolaei · Miguel A. Carreira-Perpinan -
2016 Poster: Efficient Neural Codes under Metabolic Constraints »
Zhuo Wang · Xue-Xin Wei · Alan A Stocker · Daniel Lee -
2016 Poster: Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning »
Gang Niu · Marthinus Christoffel du Plessis · Tomoya Sakai · Yao Ma · Masashi Sugiyama -
2016 Poster: Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution »
Christopher W Lynn · Daniel Lee -
2015 Poster: A fast, universal algorithm to learn parametric nonlinear embeddings »
Miguel A. Carreira-Perpinan · Max Vladymyrov -
2014 Workshop: Novel Trends and Applications in Reinforcement Learning »
Csaba Szepesvari · Marc Deisenroth · Sergey Levine · Pedro Ortega · Brian Ziebart · Emma Brunskill · Naftali Tishby · Gerhard Neumann · Daniel Lee · Sridhar Mahadevan · Pieter Abbeel · David Silver · Vicenç Gómez -
2014 Poster: Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP »
Shinichi Nakajima · Issei Sato · Masashi Sugiyama · Kazuho Watanabe · Hiroko Kobayashi -
2014 Poster: Multitask learning meets tensor factorization: task imputation via convex optimization »
Kishan Wimalawarne · Masashi Sugiyama · Ryota Tomioka -
2014 Poster: Analysis of Learning from Positive and Unlabeled Data »
Marthinus C du Plessis · Gang Niu · Masashi Sugiyama -
2014 Poster: Efficient Structured Matrix Rank Minimization »
Adams Wei Yu · Wanli Ma · Yaoliang Yu · Jaime Carbonell · Suvrit Sra -
2013 Poster: Parametric Task Learning »
Ichiro Takeuchi · Tatsuya Hongo · Masashi Sugiyama · Shinichi Nakajima -
2013 Poster: Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering »
Shinichi Nakajima · Akiko Takeda · S. Derin Babacan · Masashi Sugiyama · Ichiro Takeuchi -
2013 Poster: Optimal Neural Population Codes for High-dimensional Stimulus Variables »
Zhuo Wang · Alan A Stocker · Daniel Lee -
2012 Poster: Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum $L_p$ Loss »
Zhuo Wang · Alan A Stocker · Daniel Lee -
2012 Poster: Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification »
Yung-Kyun Noh · Frank Park · Daniel Lee -
2012 Poster: Perfect Dimensionality Recovery by Variational Bayesian PCA »
Shinichi Nakajima · Ryota Tomioka · Masashi Sugiyama · S. Derin Babacan -
2012 Poster: Density-Difference Estimation »
Masashi Sugiyama · Takafumi Kanamori · Taiji Suzuki · Marthinus C du Plessis · Song Liu · Ichiro Takeuchi -
2011 Poster: A Denoising View of Matrix Completion »
Weiran Wang · Miguel A. Carreira-Perpinan · Zhengdong Lu -
2011 Poster: Relative Density-Ratio Estimation for Robust Distribution Comparison »
Makoto Yamada · Taiji Suzuki · Takafumi Kanamori · Hirotaka Hachiya · Masashi Sugiyama -
2011 Poster: Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification »
Ichiro Takeuchi · Masashi Sugiyama -
2011 Poster: Analysis and Improvement of Policy Gradient Estimation »
Tingting Zhao · Hirotaka Hachiya · Gang Niu · Masashi Sugiyama -
2011 Poster: Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent »
Shinichi Nakajima · Masashi Sugiyama · S. Derin Babacan -
2010 Spotlight: Global Analytic Solution for Variational Bayesian Matrix Factorization »
Shinichi Nakajima · Masashi Sugiyama · Ryota Tomioka -
2010 Poster: Learning via Gaussian Herding »
Yacov Crammer · Daniel Lee -
2010 Poster: Global Analytic Solution for Variational Bayesian Matrix Factorization »
Shinichi Nakajima · Masashi Sugiyama · Ryota Tomioka -
2010 Poster: Generative Local Metric Learning for Nearest Neighbor Classification »
Yung-Kyun Noh · Byoung-Tak Zhang · Daniel Lee -
2008 Poster: Extended Grassmann Kernels for Subspace-Based Learning »
Jihun Hamm · Daniel Lee -
2008 Poster: Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection »
Takafumi Kanamori · Shohei Hido · Masashi Sugiyama -
2007 Oral: Blind channel identification for speech dereverberation using l1-norm sparse learning »
Yuanqing Lin · Jingdong Chen · Youngmoo E Kim · Daniel Lee -
2007 Poster: Blind channel identification for speech dereverberation using l1-norm sparse learning »
Yuanqing Lin · Jingdong Chen · Youngmoo E Kim · Daniel Lee -
2007 Poster: Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation »
Masashi Sugiyama · Shinichi Nakajima · Hisashi Kashima · Paul von Buenau · Motoaki Kawanabe -
2007 Poster: Multi-Task Learning via Conic Programming »
Tsuyoshi Kato · Hisashi Kashima · Masashi Sugiyama · Kiyoshi Asai -
2007 Poster: People Tracking with the Laplacian Eigenmaps Latent Variable Model »
Zhengdong Lu · Miguel A. Carreira-Perpinan · Cristian Sminchisescu -
2006 Workshop: Learning when test and training inputs have different distributions »
Joaquin Quiñonero-Candela · Masashi Sugiyama · Anton Schwaighofer · Neil D Lawrence -
2006 Poster: Mixture Regression for Covariate Shift »
Amos Storkey · Masashi Sugiyama