Reading Seminar on
Data Science and Compressive Sensing
formerly Compressive Sensing, Extensions, and Applications
Wednesdays at 5:30pm via Zoom.
24 Mar: Chunyang Liao presented
When do neural networks outperform kernel methods?
by B. Ghorbani, S. Mei, T. Misiakiewicz, and A. Montanari.
17 Mar: Ryan Malthaner presented
On the stability properties and the optimization landscape of training problems with squared loss for neural networks and general nonlinear conic approximation schemes.
by C. Christof
03 Mar: Bolong Ma presented
Spurious valleys in one-hidden-layer neural network optimization landscapes
by L. Venturi, A. Bandeira, J. Bruna.
24 Feb: Mahmood Ettehad presented
A well-tempered landscape for non-convex robust subspace recovery
by T. Maunu, T. Zhang, G. Lerman.
10 Feb: Chunyang Liao presented
Optimal estimation of linear operators in Hilbert spaces from inaccurate data
by A. Melkman and C. Micchelli
Optimal estimation of linear operators from inaccurate data: A second look
by C. Micchelli
03 Feb: Tushar Pandey presented
Explicit frames for deterministic phase retrieval via PhaseLift
by M. Kech.
27 Jan: Simon Foucart presented
Optimal approximation of continuous functions by very deep ReLU networks
by D. Yarotsky.
Wednesdays at 5:00pm via Zoom.
28 Oct: Kung-Ching Lin presented
Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks
by P. Bartlett, N. Harvey, C. Liaw, and A. Mehrabian.
21 Oct: Josiah Park presented
Polynomial codes: an optimal design for high-dimensional coded matrix multiplication
by Q. Yu, M. Ali Maddah-Ali, and A. S. Avestimehr.
14 Oct: Mahmood Ettehad presented
Nonlinear reduced models for state and parameter estimation
by A. Cohen, W. Dahmen, O.  Mula, and J. Nichols.
07 Oct: Tushar Pandey presented
Unbalanced expanders and randomness extractors from Parvesh-Vardy codes
by V. Guruswami, C. Vadhan, and S. Umans.
30 Sep: Bolong Ma presented
Dense quantum measurement theory
by L. Gyongyosi and S. Imre.
23 Sep: Ryan Malthaner presented
Memory capacity of neural networks with threshold and ReLU activations
by R. Vershynin
16 Sep: Srinivas Subramanian presented
Efficient projections onto the l1-ball for learning in high dimensions
by J. Duchi, S. Shalev-Shwartz, Y. Singer
and T. Chandra
Sparse projections onto the simplex
by A. Kyrillidis, S. Becker, V. Cevher, and C. Koch
09 Sep: Chunyang Liao presented
Regularization in regression with bounded noise: a Chebyshev center approach
by A. Beck and Y. Eldar.
02 Sep: Kung-Ching Lin talked about
Signal decimation with optimal reconstruction error guarantee.
26 Aug: Simon Foucart presented
Instances of computational optimal recovery: refined approximability models.(doi)
Tuesdays at 4:00pm in Blocker 608M.
03 Mar: Chunyang Liao presented
Learning to benchmark: determining best achievable misclassification error from training data
by M. Noshad, L. Xu, and A. Hero.
25 Feb: Bolong Ma presented
Multilinear compressive sensing and an
application to convolutional linear networks
by F.Malgouyres and J. Landsberg.
18 Feb: Mahmood Ettehad presented
Optimal sampling rates for approximating analytic functions from pointwise samples
by B. Adcock, R. Platte, and A. Shadrin.
11 Feb: Srinivas Subramanian presented
Multi-layer sparse coding: the holistic way
by A. Aberdam, J. Sulam, and M. Elad.
04 Feb: Ryan Malthaner presented
Deep network approximation for smooth functions
by J. Lu, Z. Shen, H. Yang, and S. Zhang.
28 Jan: Simon Foucart presented
Facilitating OWL norm minimizations.
Wednesdays at 5:00pm in Blocker 608M.
20 Nov: Ming Wei presented
Universal matrix completion,
by S. Bhojanapalli and P. Jain.
13 Nov: Qi Yuan presented
Random gradient extrapolation for distributed and stochastic optimization,
by G. Lan and Y. Zhou.
06 Nov: Jiangyuan Li presented
Surprises in High-Dimensional Ridgeless Least Squares Interpolation,
by T. Hastie, A. Montanari, S. Rosset, and R. J. Tibshirani.
30 Oct: Srinivas Subramanian presented
Reliable recovery of hierarchically sparse signals and application in machine-type communications,
by I. Roth, M. Kliesch, G. Wunder, and J. Eisert
23 Oct: Simon Foucart discussed
Determinism in compressive data acquisition.
09 Oct: Chunyang Liao presented
ReLU deep neural networks and linear finite elements,
by J. He, L. Li, J. Xu, and C. Zheng.
02 Oct: Ryan Malthaner presented
Nonlinear approximation via compositions,
by Z. Shen, H. Yang, and S. Zhang.
25 Sep: Bolong Ma presented
Deep neural network approximation theory,
by P. Grohs, D. Perekrestenko, D. Elbrächter, and H. Bölcskei.
18 Sep: Mahmood Ettehad presented
Just interpolate: kernel "ridgeless" regression can generalize,
by T. Liang and A. Rakhlin.
11 Sep: Srinivas Subramanian presented
Algorithmic regularization in over-parameterized matrix sensing and neural networks with quadratic activations,
by Y. Li, T. Ma, and H. Zhang.
04 Sep: Simon Foucart presented
Sampling schemes and recovery algorithms for functions of few coordinate variables.
Fridays at 3:40pm in Blocker 608M.
02 Nov: Jiangyuan Li presented
Algorithmic aspects of inverse problems using generative models,
by C. Hegde.
26 Oct: Rick Lynch presented
Preserving injectivity under subgaussian mappings and its application to compressed sensing,
by G. Casazza, X. Chen, and himself.
19 Oct: Srinivas Subramanian presented
Modeling sparse deviations for compressed sensing using generative models,
by M. Dhar, A. Grover, and S. Ermon.
05 Oct: Ryan Malthaner presented
A compressed sensing view of unsupervised text embeddings, bag-of-n-grams, and LSTMs,
by S. Arora, M. Khodak, N. Saunshi, and K. Vodrahalli.
28 Sep: Simon Foucart talked about
Semidefinite programming in approximation theory: two examples.
21 Sep: Bolong Ma presented
Mad Max: affine spline insights into deep learning,
by R. Balestriero and R. Baraniuk.
14 Sep: Mahmood Ettehad presented
Learning without mixing: towards a sharp analysis of linear system identification,
by M. Simchowitz, H. Mania, S. Tu, M. Jordan, and B. Recht.
Thursdays at 4:00pm, usually in Blocker 608M.
19 Apr: Ryan Malthaner presented
Generalization in machine learning via analytical learning theory,
by K. Kawaguchi and Y. Bengio.
12 Apr: Bolong Ma presented
Constructive methods of approximation by ridge functions and radial functions
by Y. Xu, W. Light, and W. Cheney.
05 Apr: Xiaojing Wang talked about
Seismic data denoising based on dictionary learning.
In Blocker 624.
08 Mar: Laurent Jacques talked about
Time for dithering! Quantized random embeddings with RIP random matrices.
In Blocker 628.
01 Mar: Xiaohan Chen talked about
Deep learning techniques in compressive sensing and optimization.
22 Feb: Rick Lynch presented
Sparse recovery under weak moment assumptions,
by G. Lecué and S. Mendelson.
08 Feb: Srinivas Subramanian presented
Normalized iterative hard thresholding for matrix completion,
by J. Tanner and K. Wei.
01 Feb: Mahmood Ettehad presented
Data assimilation in reduced modeling,
by P. Binev, A. Cohen, W. Dahmen, R. DeVore, G. Petrova, and P. Wojtaszczyk.
25 Jan: Jiangyuan Li presented
Matrix completion via max-norm constrained optimization,
by T. Cai and W.-X. Zhou.
Fridays at 4:00pm in Blocker 608M.
01 Dec: Mahmood Ettehad presented
Linear system identification via atomic norm regularization,
by P. Shah, B. N. Bhaskar, G. Tang and B. Recht.
17 Nov: Bolong Ma presented
Optimal approximation with sparsely connected deep neural networks,
by H. Bölcskei, P. Grohs, G. Kutyniok, P. Petersen.
10 Nov: Srinivas Subramanian presented
Cubature, approximation, and isotropy in the hypercube,
by Lloyd N. Trefethen.
03 Nov: Rick Lynch presented
Towards understanding the invertibility of convolutional neural networks,
by A. Gilbert, Y. Zhang, K. Lee, Y. Zhang, H. Lee.
27 Oct: Simon Foucart presented
Infinite-dimensional L1 minimization and function approximation from pointwise data,
by B. Adcock.
13 Oct: Jiangyuan Li presented
Stable optimizationless recovery from phaseless linear measurements,
by L. Demanet and P. Hand.
29 Sep: Bolong Ma presented
A mathematical theory of deep convolutional neural networks for feature extraction,
by T. Wiatowski, H. Bölcskei.
22 Sep: Rick Lynch presented
Compressed sensing using generative models,
by A. Bora, A. Jalal, E. Price, A. Dimakis.
15 Sep: Srinivas Subramanian presented
Compressed sensing from phaseless gaussian measurements via linear programming in the natural parameter space,
by P. Hand and V. Voroninski.
08 Sep: Mahmood Ettehad presented
Non-asymptotic analysis of robust control from coarse-grained identification,
by S. Tu, R. Boczar, A. Packard, and B. Recht.
01 Sep: Simon Foucart presented
Solving random quadratic systems of equations is nearly as easy as solving linear systems,
by Y. Chen and E. Candès.
Fridays at 3:00pm in Blocker 608M.
21 Apr: Simon Foucart presented
An IHT algorithm for sparse recovery from subexponential measurements,
by S. Foucart and G. Lecué.
03 Mar: Jiangyuan Li presented
One-bit compressed sensing with non-Gaussian measurements,
by A. Ai, A. Lapanowski, Y. Plan, and R. Vershynin.
24 Feb: Mahmood Ettehad presented
A simpler approach to matrix completion,
by B. Recht.
17 Feb: Srinivas Subramanian presented
Recent developments in the sparse Fourier transform: a compressed Fourier transform for big data,
by A. Gilbert, P. Indyk, M. Iwen, and L. Schmidt.
10 Feb: Xinjie Fan presented
Minimax lower bounds on dictionary learning for tensor data,
by Z. Shakeri, W. Bajwa, and A. Sarwate.
03 Feb: Rick Lynch presented
Online dictionary learning for sparse coding,
by J. Mairal, F. Bach, J. Ponce, and G. Sapiro.
27 Jan: Simon Foucart presented
Sparse recovery from saturated measurements,
by S. Foucart and T. Needham.
Wednesdays at 4:00pm in Blocker 608M.
07 Dec: Xinjie Fan presented
The generalized Lasso with non-linear observations,
by Y. Plan and R. Vershynin.
30 Nov: Srinivas Subramanian presented
Orthogonal matching pursuit under the restricted isometry property,
by A. Cohen, W. Dahmen, and R. DeVore.
16 Nov: Mahmood Ettehad presented
Sparse and spurious: dictionary learning with noise and outliers,
by R. Gribonval, R. Jenatton and F. Bach.
9 Nov: Rick Lynch presented
Compressive sensing with redundant dictionaries and structured measurements,
by F. Krahmer, D. Needell, and R. Ward.
2 Nov: Simon Foucart presented
A least-squares method for sparse low rank approximation of multivariate functions,
by M. Chevreuil, R. Lebrun, A. Nouy, and P. Rai.
26 Oct: Xinjie Fan presented
A Tight Bound of Hard Thresholding, by J. Shen and P. Li.
19 Oct: Srinivas Subramanian presented
GPU accelerated greedy algorithms for compressed sensing,
by J. Blanchard and J. Tanner.
12 Oct: Mahmood Ettehad presented
Link delay estimation via expander graphs,
by M. Firooz and S. Roy.
5 Oct: Rick Lynch presented
A conditional construction of restricted isometries,
by A. Bandeira, D. Mixon, and J. Moreira.
21 Sep: Simon Foucart presented
Improving compressed sensing with the diamond norm,
by M. Kliesch, R. Kueng, J. Eisert, and D. Gross.
14 Sep: David Koslicki (Oregon State University) presented
Quikr: a method for rapid reconstruction of bacterial communities via compressive sensing,
by D. Koslicki, S. Foucart, and G. Rosen,
as well as
Sparse recovery by means of nonnegative least squares,
by S. Foucart and D. Koslicki.
Thursdays at 3:00pm in Blocker 608M.
21 Apr: Srinivas Subramanian presented
Message-passing algorithms for compressed sensing,
by D. L. Donoho, A. Maleki, and A. Montanari.
14 Apr: Mahmood Ettehad presented
Exact reconstruction of gene regulatory networks using compressive sensing,
by Y. Chang, J. Gray, and C. Tomlin.
31 Mar: Xinjie Fan presented
Robust subspace clustering,
by M. Soltanolkotabi, E. Elhamifar, and E. Candès.
24 Mar: Simon Foucart presented
When are Quasi-Monte Carlo algorithms efficient for high dimensional integrals?,
by I. Sloan and H. Woźniakowski.
10 Mar: Srinivas Subramanian presented
by R. Mendoza-Smith and J. Tanner.
3 Mar: Mahmood Ettehad presented two papers by
B. Sanandaji, T. Vincent, and M. Wakin.
25 Feb: Avinash Vem presented
Sub-linear time compressed sensing for support recovery using sparse-graph codes
by X. Li, S. Pawar, and K. Ramchandran.
18 Feb: Xinjie Fan presented
On the fundamental limits of adaptive sensing,
by E. Arias-Castro, E. Candès, and M. Davenport.
11 Feb: Simon Foucart presented
Sparse disjointed recovery from noninflating measurements,
by S. Foucart, M. Minner, and T. Needham.
Thursdays at 4:00pm in Blocker 628.
01 Oct: Overview of the Mathematics of Compressive Sensing - Part 1, presented by Simon Foucart.
08 Oct: Overview of the Mathematics of Compressive Sensing - Part 2, presented by Simon Foucart.
15 Oct: Overview of the Mathematics of Compressive Sensing - Part 3, presented by Simon Foucart.
29 Oct: Overview of the Mathematics of Compressive Sensing - Part 4, presented by Simon Foucart.
05 Nov: Nathan LaFerney presented
Living on the edge: phase transitions in convex programs with random data,
by D. Amelunxen, M. Lotz, M. McCoy, and J. Tropp.
19 Nov: Srinivas Subramanian presented
Efficient and robust compressed sensing using optimized expander graphs,
by S. Jafarpour, W. Xu, B. Hassibi, and R. Calderbank.
03 Dec: Simon Foucart presented
Sparse Estimation with Strongly Correlated Variables using Ordered Weighted L1 Regularization,
by M. Figueiredo and R. Nowak.