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|---|---|---|---|---|---|---|---|---|---|---|---|
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0804.1448v1.1 | 0804.1448 | Fast k Nearest Neighbor Search using GPU | [
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0903.0843v2.3 | 0903.0843 | Algorithms for Weighted Boolean Optimization | [
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0903.0843v2.4 | 0903.0843 | Algorithms for Weighted Boolean Optimization | [
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0905.0586v1.1 | 0905.0586 | WinBioinfTools: Bioinformatics Tools for Windows High Performance Computing Server 2008 | [
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0905.0586v1.2 | 0905.0586 | WinBioinfTools: Bioinformatics Tools for Windows High Performance Computing Server 2008 | [
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0905.0586v1.4 | 0905.0586 | WinBioinfTools: Bioinformatics Tools for Windows High Performance Computing Server 2008 | [
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0905.0794v5.2 | 0905.0794 | Constructions of Almost Optimal Resilient Boolean Functions on Large Even Number of Variables | [
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0906.0231v3.1 | 0906.0231 | Solving $k$-Nearest Neighbor Problem on Multiple Graphics Processors | [
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0908.3280v2.2 | 0908.3280 | On the Relationship between Trading Network and WWW Network: A Preferential Attachment Perspective | [
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0908.3280v2.3 | 0908.3280 | On the Relationship between Trading Network and WWW Network: A Preferential Attachment Perspective | [
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0909.1594v1.3 | 0909.1594 | Computation and Dynamics: Classical and Quantum | [
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1003.0487v1.1 | 1003.0487 | Scalable Large-Margin Mahalanobis Distance Metric Learning | [
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1003.0487v1.2 | 1003.0487 | Scalable Large-Margin Mahalanobis Distance Metric Learning | [
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1003.0487v1.3 | 1003.0487 | Scalable Large-Margin Mahalanobis Distance Metric Learning | [
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1004.5186v1.1 | 1004.5186 | Multiscale approach for the network compression-friendly ordering | [
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1006.2734v1.1 | 1006.2734 | Penalized K-Nearest-Neighbor-Graph Based Metrics for Clustering | [
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1007.0920v1.1 | 1007.0920 | End-Host Distribution in Application-Layer Multicast: Main Issues and Solutions | [
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1007.0920v1.2 | 1007.0920 | End-Host Distribution in Application-Layer Multicast: Main Issues and Solutions | [
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1008.5387v1.2 | 1008.5387 | Pattern Recognition in Collective Cognitive Systems: Hybrid Human-Machine Learning (HHML) By Heterogeneous Ensembles | [
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"Amir H. Assadi"
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"... | |
1010.2296v1.1 | 1010.2296 | Rainbow Connection Number and Connected Dominating Sets | [
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{
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"... | |
1101.0039v1.1 | 1101.0039 | A Brief Review on Results and Computational Algorithms for Minimizing the Lennard-Jones Potential | [
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] | CC-BY-NC-SA | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDE1OTcgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjarZrLbt02EED3/oq7tBdiOQ9yyG2AdpFFgaLeBVmkjQMUzQNpkub3O6pFQe6lpiY4MODntQ4vj8h5iJ9v4BL1Ay6QS+Akl4wSENPl9w83r17Hy1v948tLDFTL5fu/L/1wQeFARPr9+8uvN7/cfL6+CKQQxbqGvhpCTWm7xIv7mx9+KpcaasZ8uX93AWUwJb1SCVmveP/28ur2528f7rDc/na... | [
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"... | |
1102.0048v2.1 | 1102.0048 | Smart depth of field optimization applied to a robotised view camera | [
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"Olivier Mondin"
] | CC-BY | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDQzNSAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjarZQ/T+RADMX7fIopocB4bM+M3d4JCjp0KxqgQCAq/ggJ6b7+OWThMrthRJJVmijz9N486xe/dTGgPzEQFyhsQQqBooT75+76FsODH14EBDYNfz+kzyFygpLN35/Cn+6ye9s3yQhZrGXi8giW0tbj16Y7PddgYJly2DwGEoYSi1sJEPunh3B99Pv15Zj06P3u/v34dnPRnW3G4epKLUvDYxy... | [
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"... | |
1102.0048v2.2 | 1102.0048 | Smart depth of field optimization applied to a robotised view camera | [
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"... | |
1103.0412v2.1 | 1103.0412 | Counting large distances in convex polygons | [
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"... | |
1105.1436v1.2 | 1105.1436 | Solving Rubik's Cube Using SAT Solvers | [
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] | CC-BY-NC-SA | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDY3NiAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjarZdLb9swEITv/hU82gdvyV0+dq8F2kNuRX1Lc3ATpymQRwO76N/vyjEJyQ8qAYUcHFgyv9nhaCS9zpyx+ueMiw4wRROcAwnJ3D7Nrm+sudODV8YCCZt/+1OfDDJDlKj/P5rvs2+z19NFrIBE/5FFPq9mn76y6X6H0azuda0AGJ2u5YBdMKs7cz2//ftzsUSebxZLIppvd+vdZnGzupp9WfV... | [
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"... | |
1105.1436v1.3 | 1105.1436 | Solving Rubik's Cube Using SAT Solvers | [
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"... | |
1106.1372v1.1 | 1106.1372 | Phase Selection Heuristics for Satisfiability Solvers | [
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"text": "#clauses"... | [
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"... | |
1107.1058v1.1 | 1107.1058 | Online Vehicle Detection For Estimating Traffic Status | [
"Ranch Y. Q. Lai"
] | CC-BY-NC-SA | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDgzOSAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjatZhNT9tAEIbv+RV7dA6Z7s7s5xUJVKH20BL1AhxCYkIkYoOJVMGv7zgOqU2sbZ0NQgoElnnf2Xlmdp3nkRKSv5RQloCU0CGAkyTm69H1rRQL/tulkEDBi9/blWuBXoNFzz8/iqvRj9HzQQzvwOgQi8GrFQRjdiHOpqMvF14ECBatmN5zpADoPdtRoMiI6UJcZ1ev6zH67G484dfycXw7vRy... | [
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"tex": "$\\Gamma ({h_3})$",
"content": [
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... | [
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"... | |
1108.3614v1.2 | 1108.3614 | Feature Reinforcement Learning In Practice | [
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{
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1108.3915v3.3 | 1108.3915 | City on the Sky: Flexible, Secure Data Sharing on the Cloud | [
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"Wang Wenqiang",
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1108.3915v3.5 | 1108.3915 | City on the Sky: Flexible, Secure Data Sharing on the Cloud | [
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1108.3915v3.6 | 1108.3915 | City on the Sky: Flexible, Secure Data Sharing on the Cloud | [
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"Wang Wenqiang",
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1108.4723v1.1 | 1108.4723 | Self-Optimized OFDMA via Multiple Stackelberg Leader Equilibrium | [
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"Jianjun Hou"
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1108.4723v1.2 | 1108.4723 | Self-Optimized OFDMA via Multiple Stackelberg Leader Equilibrium | [
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"Jianjun Hou"
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1108.4723v1.3 | 1108.4723 | Self-Optimized OFDMA via Multiple Stackelberg Leader Equilibrium | [
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1109.4653v2.11 | 1109.4653 | Can the evolution of music be analyzed in a quantitative manner? | [
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"... | |
1109.4653v2.12 | 1109.4653 | Can the evolution of music be analyzed in a quantitative manner? | [
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"Renato Fabbri",
"Gonzalo Travieso",
"Luciano da Fontoura Costa"
] | other:http://creativecommons.org/licenses/publicdomain/ | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDU4MiAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjatZdPb9pAEMXv/hTbGxwy3dnZv8dWTQ+pVLWqb1EOFlBh1QkEu6rEp++YUNfgZGOzirjB8Jh578fs+jFDIfmFAonAWS+0l0DOiMV9dnsnxZI/vBH8VvDiz6H0XihpQFH7xUr8yL5nj0MR60EpjIlwOUIw5qjxMc/ef/YiQLDKivynQKcAjRLaIXjpRb4Ut7Nv67La1JvtulwU1fyKiGb53NN... | [
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"... | |
1109.4653v2.8 | 1109.4653 | Can the evolution of music be analyzed in a quantitative manner? | [
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"Renato Fabbri",
"Gonzalo Travieso",
"Luciano da Fontoura Costa"
] | other:http://creativecommons.org/licenses/publicdomain/ | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDcxMCAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjarZdNbxpBDIbv/IrpDQ64M/Z8Wb1Fag+RcqiC1EOUA0qooElAAdKq/fX18rFZNssU4orLSOv1a7/zjHd47jlj5eeMI4IUs/E5AgUyd0+9m1tr7uXhpbFAnM2vTeiTQcuQA8r60Vz3vvae3yZJHhxzKYmEO+AQdjkuRr2PX7Jh4IjRjL4bFzNYFyRVgpSDGd2bm/7Vy2p2N34cDImof7UYYOr... | [
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{
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"... | |
1109.4653v2.9 | 1109.4653 | Can the evolution of music be analyzed in a quantitative manner? | [
"Vilson Vieira",
"Renato Fabbri",
"Gonzalo Travieso",
"Luciano da Fontoura Costa"
] | other:http://creativecommons.org/licenses/publicdomain/ | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDU5NiAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjavZdNb9pAEIbv/hXbGz4w3dnZ2Y9rpPYQKYcqvkU5WOAKxFcDpFX767sm4BhwNphNKw5G7PAy+76Pd8xThkKGFwokAmuc0E4CWRajRfbwKMU4LN6K8JF34teudCGUksDE4f1c3GffsqdzEeNAKYyJhHIEz7zXuCmyz1+d8OCNMqL4LtCHZVRCWwQnnSjG4mFw97yZjsp5PiSiQZE7GqynP+Z... | [
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"text": "Mo... | [
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"... | |
1110.3094v1.3 | 1110.3094 | Syndromic classification of Twitter messages | [
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1201.0846v1.1 | 1201.0846 | Using complex surveys to estimate the $L_1$-median of a functional variable: application to electricity load curves | [
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1201.0846v1.3 | 1201.0846 | Using complex surveys to estimate the $L_1$-median of a functional variable: application to electricity load curves | [
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1201.0846v1.5 | 1201.0846 | Using complex surveys to estimate the $L_1$-median of a functional variable: application to electricity load curves | [
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1201.2969v1.4 | 1201.2969 | SparseDTW: A Novel Approach to Speed up Dynamic Time Warping | [
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1203.5066v1.1 | 1203.5066 | A Corpus-based Study of Temporal Signals | [
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1203.5073v1.1 | 1203.5073 | USFD at KBP 2011: Entity Linking, Slot Filling and Temporal Bounding | [
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1203.5073v1.10 | 1203.5073 | USFD at KBP 2011: Entity Linking, Slot Filling and Temporal Bounding | [
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1203.5073v1.2 | 1203.5073 | USFD at KBP 2011: Entity Linking, Slot Filling and Temporal Bounding | [
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1203.5073v1.3 | 1203.5073 | USFD at KBP 2011: Entity Linking, Slot Filling and Temporal Bounding | [
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1203.5073v1.6 | 1203.5073 | USFD at KBP 2011: Entity Linking, Slot Filling and Temporal Bounding | [
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1203.5076v1.1 | 1203.5076 | Massively Increasing TIMEX3 Resources: A Transduction Approach | [
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1203.5076v1.4 | 1203.5076 | Massively Increasing TIMEX3 Resources: A Transduction Approach | [
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1204.1995v1.16 | 1204.1995 | Attribute Exploration of Gene Regulatory Processes | [
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1204.3731v1.1 | 1204.3731 | Towards Real-Time Summarization of Scheduled Events from Twitter Streams | [
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1206.3992v3.1 | 1206.3992 | Evaluating Overlapping Communities with the Conductance of their Boundary Nodes | [
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1208.2113v1.1 | 1208.2113 | Stochastic linear programming with a distortion risk constraint | [
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1209.3126v1.1 | 1209.3126 | Beyond Stemming and Lemmatization: Ultra-stemming to Improve Automatic Text Summarization | [
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1209.3126v1.10 | 1209.3126 | Beyond Stemming and Lemmatization: Ultra-stemming to Improve Automatic Text Summarization | [
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1209.3126v1.8 | 1209.3126 | Beyond Stemming and Lemmatization: Ultra-stemming to Improve Automatic Text Summarization | [
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1301.0216v1.1 | 1301.0216 | Applying Strategic Multiagent Planning to Real-World Travel Sharing Problems | [
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1301.0302v2.1 | 1301.0302 | MANCaLog: A Logic for Multi-Attribute Network Cascades (Technical Report) | [
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1301.2698v1.2 | 1301.2698 | Evaluating community structure in large network with random walks | [
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1301.3614v3.2 | 1301.3614 | Joint Space Neural Probabilistic Language Model for Statistical Machine Translation | [
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1302.4519v1.4 | 1302.4519 | A Genetic Algorithm for Power-Aware Virtual Machine Allocation in Private Cloud | [
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1302.7008v2.1 | 1302.7008 | Measuring the Size of Large No-Limit Poker Games | [
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1302.7278v2.1 | 1302.7278 | Using cascading Bloom filters to improve the memory usage for de Brujin graphs | [
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1303.0270v1.1 | 1303.0270 | Computable Compressed Matrices | [
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1303.0270v1.3 | 1303.0270 | Computable Compressed Matrices | [
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1303.0270v1.4 | 1303.0270 | Computable Compressed Matrices | [
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1303.0270v1.5 | 1303.0270 | Computable Compressed Matrices | [
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1303.0875v1.2 | 1303.0875 | LT^2C^2: A language of thought with Turing-computable Kolmogorov complexity | [
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"... | |
1305.1199v4.1 | 1305.1199 | How to find real-world applications for compressive sensing | [
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1306.4044v2.1 | 1306.4044 | Attack Planning in the Real World | [
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1307.7382v1.1 | 1307.7382 | Learning Frames from Text with an Unsupervised Latent Variable Model | [
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1307.7807v1.3 | 1307.7807 | Finite-State Markov Modeling of Tunnel Channels in Communication-based Train Control (CBTC) Systems | [
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"Tao Tang",
"Bin Ning"
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"... | |
1308.6198v3.1 | 1308.6198 | PDA: Semantically Secure Time-Series Data Analytics with Dynamic Subgroups | [
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1308.6198v3.2 | 1308.6198 | PDA: Semantically Secure Time-Series Data Analytics with Dynamic Subgroups | [
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"Junze Han",
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1308.6687v1.1 | 1308.6687 | Image Set based Collaborative Representation for Face Recognition | [
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"Lei Zhang",
"Simon C. K. Shiu",
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] | CC-BY-NC-SA | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDU4MiAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjatZRNc5swEIbv/Aod4eCtPlZf16bNtOmptm9JDgQTlynGCThtp7++CwZqT8bYGbXDRSOJ3VfP7r7PkWCcPsGE1iCdZugdOG5Ytolu7zlb0eEN46C8Yz+7qxumOAdjHa1Ltoi+Ru+X0btroZkDbwyy5SMTDsFbT8E4eGXYcsVu48+L63lyv7yJPi6j5zGvVBq8MAydBYNuKi9dp3Dan0wrHZ2... | [
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... | [
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"... | |
1309.0302v1.2 | 1309.0302 | Unmixing Incoherent Structures of Big Data by Randomized or Greedy Decomposition | [
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"Dacheng Tao"
] | CC-BY-NC-SA | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDM3MSAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjarVTLbsJADLznK/YIB8za3mePtKUVUiUquCEOCOhDgoaX1N+vm5CWtiEqBK0iWdnZ8diz3nWCSstCRdqBcUHJB2hZTZfJaKzVTDZ7SgPHoN4z6FJhDMBIEi/UIHlM1t8kPoDxThlrIcZYRSJwhGjtnqMzTNrdoCJER04NnxQFA0Z0GBvBBvk1U6NG/7rfbCFp3bhLb+bTIt7MO9tl2hwPe8n... | [
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{
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1309.7912v1.1 | 1309.7912 | An Image-Based Fluid Surface Pattern Model | [
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"Ricardo Fabbri",
"Lucia Maria dos Santos Pinto",
"Francisco Duarte Moura Neto"
] | CC-BY | train | false | "JVBERi0xLjUKJdDUxdgKMyAwIG9iago8PAovTGVuZ3RoIDQwOCAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjarZXLTsMwEEX3+Qovk0UHjz0e20uQAIkdanaIRdQUVAkoLa/fZygoDUowTVJlk4d1Z+49Y2eTodJyoUJvwVlWxBGCYbV4zG5utarl45XSYGNQH7ulj8owAXqW+wc1z66zTVfEeWBvUiKyHCE619EwVoMjmqhhpA8/QuOszE4u0KkIkSWF8k60AjiUfhjBuKDKWt3kp++FNflyW90vi5kNNq9... | [
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"y2": 505.6802978515625
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{
"text": "... | [
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{
"id": 41,
"tex": "Amsterdam, NL",
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1312.4477v1.2 | 1312.4477 | GCG: Mining Maximal Complete Graph Patterns from Large Spatial Data | [
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{
"text": "Table1:TheSDSSschema",
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{
"id": 22,
"tex": "cz",
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1312.4477v1.3 | 1312.4477 | GCG: Mining Maximal Complete Graph Patterns from Large Spatial Data | [
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{
"text": "Table1:Example:Datasetoftwodimensions.",
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{
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1312.6549v1.1 | 1312.6549 | Some considerations about Java implementation of two provably secure pseudorandom bit generators | [
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{
"text": "QUADimplementation",
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{
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1312.6549v1.4 | 1312.6549 | Some considerations about Java implementation of two provably secure pseudorandom bit generators | [
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1312.6549v1.5 | 1312.6549 | Some considerations about Java implementation of two provably secure pseudorandom bit generators | [
"Corbo Antonio Esposito",
"Didone Fabiola"
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"text": "10 3 Modularreductions",
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... | [
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