Since the last Nuit Blanche in Review (February 2016) I somehow wrote the 4000th post on Nuit Blanche and we presented our paper at ICASSP (ICASSP poster: Random Projections through multiple optical scattering: Approximating kernels at the speed of light). On Nuit Blanche, we also had three implementation, some CS hardware, a few in-depth papers with an emphasis on streaming/hashing but also CS phase retrieval and more. Enjoy !
Implementation
Implementation
Hardware
- Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder
- Single-pixel 3D imaging with time-based depth resolution / On-chip spiral spectrometer
- CS Hardware: The InView223, A Controllable Spatial Light Modulator System
- ACDC: A Structured Efficient Linear Layer - implementation -
In-depth
CS and Phase retrieval
- Compressive sensing in medical imaging
- There something about being positive: Robust Nonnegative Sparse Recovery and the Nullspace Property of 0/1 Measurements
- Overcoming The Limitations of Phase Transition by Higher Order Analysis of Regularization Techniques
- Near-Optimal Sample Complexity Bounds for Circulant Binary Embedding
- ICASSP: Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach
- Provable Non-convex Phase Retrieval with Outliers: Median Truncated Wirtinger Flow
ML/Streaming/Hashing
- Streaming Algorithms for News and Scientific Literature Recommendation: Submodular Maximization with a d-Knapsack Constraint
- New Algorithms for Heavy Hitters in Data Streams
- An Optimal Algorithm for l1-Heavy Hitters in Insertion Streams and Related Problems / BPTree: an $\ell_2$ heavy hitters algorithm using constant memory / Approximate Hamming distance in a stream
- Exact Weighted Minwise Hashing in Constant Time
- Searching for Topological Symmetry in Data Haystack XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
- Deep Fully-Connected Networks for Video Compressive Sensing
- Scalable and Sustainable Deep Learning via Randomized Hashing
- Fast Cross-Polytope Locality-Sensitive Hashing
- Saturday Morning Video: Tutorial on Practical Methods for BigData, Hashing Algorithms for Large-Scale Search and Learning / 0-Bit Consistent Weighted Sampling, Ping Li
- A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition
Meetings
- Deep Learning Summer School, Montreal, August 2016 and Paper submission to iTWIST
- CfP: ITWIST’16 – international Traveling Workshop on Interactions between Sparse models and Technology” (iTWIST)
Paris Machine Learning meetup
- Ce Soir Paris Machine Learning Meetup #10 Season 3, M&A, Speech Recognition, Telecoms, Mariana DL & HR
- Paris Machine Learning Newsletter, March 2016 [In French]
Saturday Morning Videos
- Saturday Morning Video: Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
- Saturday Morning Video: Tutorial on Practical Methods for BigData, Hashing Algorithms for Large-Scale Search and Learning / 0-Bit Consistent Weighted Sampling, Ping Li
- Saturday Morning Video: The Code That Runs Our Lives , Geoff Hinton
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