1 Introduction 2 Unsupervised Hashing 3 Supervised Hashing 4 Ranking-based Hashing 5 Multimodal Hashing 6 Deep Hashing 7 Quantization 8 Conclusion 9 Reference

1 Introduction 2 Learning to Hash Isotropic Hashing Scalable Graph Hashing with Feature Transformation Supervised Hashing with Latent Factor Models Column Sampling based Discrete Supervised Hashing Deep Supervised Hashing with Pairwise Labels Supervised Multimodal Hashing with SCM Multiple-Bit Quantization 3 Distributed Learning Coupled Group Lasso for Web-Scale CTR Prediction Distributed Power-Law Graph Computing 4 Stochastic Learning Fast Asynchronous Parallel Stochastic Gradient Descent Distributed Stochastic ADMM for Matrix Factorization 5 Conclusion

1 Introduction Problem Definition Existing Methods 2 Scalable Graph Hashing with Feature Transformation Motivation Model and Learning Experiment 3 Conclusion 4 Reference

1 Introduction Problem Definition Existing Methods 2 Isotropic Hashing 3 Supervised Hashing with Latent Factor Model 4 Supervised Multimodal Hashing with SCM 5 Multiple-Bit Quantization Double-Bit Quantization Manhattan Quantization 6 Conclusion 7 Reference

1 Introduction 2 Learning to Hash Isotropic Hashing Supervised Hashing with Latent Factor Models Supervised Multimodal Hashing with SCM Multiple-Bit Quantization 3 Distributed Learning Coupled Group Lasso for Web-Scale CTR Prediction Distributed Power-Law Graph Computing 4 Stochastic Learning Distributed Stochastic ADMM

1 Introduction Problem Definition Existing Methods 2 Isotropic Hashing Model Learning Experiment 3 Multiple-Bit Quantization Double-Bit Quantization Manhattan Quantization 4 Conclusion 5 Reference

1 Introduction Problem Definition Existing Methods Motivation and Contribution 2 Isotropic Hashing Model Learning Experimental Results 3 Multiple-Bit Quantization Double-Bit Quantization Manhattan Quantization 4 Conclusion 5 Reference

1 Introduction 2 AsySVRG 3 SCOPE 4 Conclusion

I. Program Analysis II. Data Flow Analysis ✓ Available Expressions ✓ Liveness Analysis ✓ Reaching Definitions ✓ Very Busy Expressions III.Theory Behind IV. Sensitivity V. Summary

• Background • Software Security: Control-flow Hijack Attack ➢ Memory Layout , Stack frame, & Procedure ➢ Buffer Overflow: Vulnerability, & Defenses ➢ RILC, Return-Oriented Programming ➢ ASLR & CFI • Software Security: Non-control Data Attack ➢ Data Oriented Programming • Summary