COMS 4774 Assigned Papers

	A	B	C	D	E
1	Team member 1	Team member 2	Paper title	Link	Comment

2	Qingyang Wu	Weiyan Shi	Deep Learning with Gaussian Differential Privacy	https://arxiv.org/abs/1911.11607	The papers you proposed had rather minimial theoretical content, so I am assigning you a different but related paper.
3	Jay Pakala	Joseph DeRose	Learning Polynomials in Few Relevant Dimensions	http://proceedings.mlr.press/v125/chen20a/chen20a.pdf
4	Kun Qian		Predicting What You Already Know Helps: Provable Self-Supervised Learning	https://arxiv.org/abs/2008.01064
5	Yaonan Jin		Settling the Sample Complexity of Single-parameter Revenue Maximization	https://arxiv.org/abs/1904.04962
6	Sophia Yao		A unified view for unsupervised representation learning with density ratio estimation	https://arxiv.org/abs/2101.02083
7	Ruohan Zong		Multi-View Clustering via Canonical Correlation Analysis	https://homes.cs.washington.edu/~sham/papers/unsup/multi_cluster.pdf
8	Lu Bin Liu	Yumeng Luo	The Spectral Method for General Mixture Models	https://epubs.siam.org/doi/abs/10.1137/S0097539704445925	Please read the journal version of this paper
9	Tanner Treasure		Learning in implicit generative models	https://arxiv.org/abs/1610.03483
10	Haoran Pu		Beyond Locality-Sensitive Hashing	https://arxiv.org/abs/1306.1547
11	Chloe Cao	Xuan Zhao	Multi-View Regression via Canonical Correlation Analysis	https://homes.cs.washington.edu/~sham/papers/ml/regression_cca.pdf
12	Han Wang	Hao-Ting Wei	Why Are Big Data Matrices Approximately Low Rank?	https://epubs.siam.org/doi/10.1137/18M1183480
13	Xingxing Geng	Yunke Zhao	Performance of Johnson–Lindenstrauss Transform for k-Means and k-Medians Clustering	https://arxiv.org/abs/1811.03195
14	Anushri Arora	Viren Bajaj	Performance guarantees for regularized maximum entropy density estimation	http://www.rob.schapire.net/papers/maxent_colt.pdf	The papers you proposed had no theoretical content, so I am assigning you a different paper.
15	Ahmed Sheta	Angela Wang	Clustering with t-SNE, provably	http://arxiv.org/abs/1706.02582
16	Mohammadamin Nejatbakhshesfahani	Ali Ebrahimpour Boroojeny	A Theoretical Analysis of Contrastive Unsupervised Representation Learning	http://proceedings.mlr.press/v97/saunshi19a/saunshi19a.pdf
17	Charlotte Rochereau	Maxime Faucher	Do GANs learn the distribution? Some Theory and Empirics	https://openreview.net/forum?id=BJehNfW0-
18	Naimu Deng		Random projection trees for vector quantization	https://cseweb.ucsd.edu/~dasgupta/papers/vq.pdf
19	Chenjie Deng	Karen Jan	On Variational Bounds of Mutual Information	https://arxiv.org/abs/1905.06922
20	Sebastian Salazar		Learning Manifold Implicitly via Explicit Heat-Kernel Learning	https://arxiv.org/abs/2010.01761	Please read the full (arxiv) version of the paper
21	Michael Fagan		Convergence of Laplacian eigenmaps	http://people.cs.uchicago.edu/~niyogi/papersps/eigconv_Feb15.pdf
22	Yinuo Jin		Wasserstein GAN	https://arxiv.org/abs/1701.07875	Please read the full (arxiv) version of the paper
23	Sean Harris		Provable Bounds for Learning Some Deep Representations	https://arxiv.org/abs/1310.6343
24	Kyung Chae Park	Yunbo Liang	Isotropic PCA and affine-invariant clustering	https://arxiv.org/abs/0804.3575
25	Ling Lan		Fourier PCA and Robust Tensor Decomposition	https://arxiv.org/abs/1306.5825