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2020 – today
- 2024
[c36]Atasi Panda, Anand Louis, Prajakta Nimbhorkar:
Individual Fairness under Group Fairness Constraints in Bipartite Matching - One Framework to Approximate Them All. IJCAI 2024: 175-183- [c35]Sruthi Gorantla
, Eshaan Bhansali, Amit Deshpande, Anand Louis:
Optimizing Learning-to-Rank Models for Ex-Post Fair Relevance. SIGIR 2024: 1525-1534 - [c34]Suprovat Ghoshal, Anand Louis:
New Approximation Bounds for Small-Set Vertex Expansion. SODA 2024: 2363-2375 - [c33]Anand Louis, Rameesh Paul, Arka Ray:
Sparse Cuts in Hypergraphs from Random Walks on Simplicial Complexes. SWAT 2024: 33:1-33:15 - [i34]Anand Louis, Alantha Newman, Arka Ray:
Improved linearly ordered colorings of hypergraphs via SDP rounding. CoRR abs/2405.00427 (2024) - 2023
- [c32]Sruthi Gorantla, Anay Mehrotra, Amit Deshpande, Anand Louis:
Sampling Individually-Fair Rankings that are Always Group Fair. AIES 2023: 205-216 - [c31]Anand Louis, Meghana Nasre, Prajakta Nimbhorkar, Govind S. Sankar:
Online Algorithms for Matchings with Proportional Fairness Constraints and Diversity Constraints. ECAI 2023: 1601-1608 - [c30]Sruthi Gorantla, Amit Deshpande, Anand Louis:
Sampling Ex-Post Group-Fair Rankings. IJCAI 2023: 409-417 - [c29]Sruthi Gorantla, Kishen N. Gowda, Amit Deshpande, Anand Louis:
Socially Fair Center-Based and Linear Subspace Clustering. ECML/PKDD (1) 2023: 727-742 - [i33]Sruthi Gorantla, Anay Mehrotra, Amit Deshpande, Anand Louis:
Sampling Individually-Fair Rankings that are Always Group Fair. CoRR abs/2306.11964 (2023) - [i32]Sruthi Gorantla, Eshaan Bhansali, Amit Deshpande, Anand Louis:
Optimizing Group-Fair Plackett-Luce Ranking Models for Relevance and Ex-Post Fairness. CoRR abs/2308.13242 (2023) - [i31]Suprovat Ghoshal, Anand Louis:
New Approximation Bounds for Small-Set Vertex Expansion. CoRR abs/2311.17001 (2023) - 2022
- [c28]Suprovat Ghoshal, Anand Louis:
Approximating CSPs with Outliers. APPROX/RANDOM 2022: 43:1-43:16 - [c27]Akash Kumar, Anand Louis, Rameesh Paul:
Exact Recovery Algorithm for Planted Bipartite Graph in Semi-Random Graphs. ICALP 2022: 84:1-84:20 - [c26]Karthik Abinav Sankararaman, Anand Louis, Navin Goyal:
Robust identifiability in linear structural equation models of causal inference. UAI 2022: 1728-1737 - [i30]Sruthi Gorantla, Amit Deshpande, Anand Louis:
Sampling Random Group Fair Rankings. CoRR abs/2203.00887 (2022) - [i29]Akash Kumar, Anand Louis, Rameesh Paul:
Exact recovery algorithm for Planted Bipartite Graph in Semi-random Graphs. CoRR abs/2205.03727 (2022) - [i28]Suprovat Ghoshal, Anand Louis:
Approximating CSPs with Outliers. CoRR abs/2205.11328 (2022) - [i27]Atasi Panda, Anand Louis, Prajakta Nimbhorkar:
Bipartite Matchings with Group Fairness and Individual Fairness Constraints. CoRR abs/2208.09951 (2022) - [i26]Sruthi Gorantla, Kishen N. Gowda, Amit Deshpande, Anand Louis:
Socially Fair Center-based and Linear Subspace Clustering. CoRR abs/2208.10095 (2022) - [i25]Govind S. Sankar, Anand Louis, Meghana Nasre, Prajakta Nimbhorkar:
Matchings Under Diversity Constraints. CoRR abs/2208.11378 (2022) - [i24]Anand Louis, Rameesh Paul, Arka Ray:
Sparse Cuts in Hypergraphs from Random Walks on Simplicial Complexes. CoRR abs/2212.13406 (2022) - 2021
- [c25]Deval Patel, Arindam Khan, Anand Louis:
Group Fairness for Knapsack Problems. AAMAS 2021: 1001-1009 - [c24]Sruthi Gorantla, Amit Deshpande, Anand Louis:
On the Problem of Underranking in Group-Fair Ranking. ICML 2021: 3777-3787 - [c23]Govind S. Sankar, Anand Louis, Meghana Nasre, Prajakta Nimbhorkar:
Matchings with Group Fairness Constraints: Online and Offline Algorithms. IJCAI 2021: 377-383 - [c22]Naganand Yadati, Tingran Gao, Shahab Asoodeh, Partha P. Talukdar, Anand Louis:
Graph Neural Networks for Soft Semi-Supervised Learning on Hypergraphs. PAKDD (1) 2021: 447-458 - [c21]Suprovat Ghoshal, Anand Louis:
Approximation Algorithms and Hardness for Strong Unique Games. SODA 2021: 414-433 - [c20]Yash Khanna, Anand Louis, Rameesh Paul:
Independent Sets in Semi-random Hypergraphs. WADS 2021: 528-542 - [i23]Yash Khanna, Anand Louis, Rameesh Paul:
Independent Sets in Semi-random Hypergraphs. CoRR abs/2104.00927 (2021) - [i22]Govind S. Sankar, Anand Louis, Meghana Nasre, Prajakta Nimbhorkar:
Matchings with Group Fairness Constraints: Online and Offline Algorithms. CoRR abs/2105.09522 (2021) - 2020
- [c19]Naganand Yadati, Vikram Nitin, Madhav Nimishakavi, Prateek Yadav, Anand Louis, Partha P. Talukdar:
NHP: Neural Hypergraph Link Prediction. CIKM 2020: 1705-1714 - [c18]Yash Khanna, Anand Louis:
Planted Models for the Densest k-Subgraph Problem. FSTTCS 2020: 27:1-27:18 - [i21]Majid Farhadi, Anand Louis, Prasad Tetali:
On the Complexity and Approximation of λ∞ Spread Constant and Maximum Variance Embedding. CoRR abs/2003.05582 (2020) - [i20]Yash Khanna, Anand Louis:
Planted Models for the Densest $k$-Subgraph Problem. CoRR abs/2004.13978 (2020) - [i19]Suprovat Ghoshal, Anand Louis:
Approximation Algorithms and Hardness for Strong Unique Games. CoRR abs/2005.08918 (2020) - [i18]Deval Patel, Arindam Khan, Anand Louis:
Group Fairness for Knapsack Problems. CoRR abs/2006.07832 (2020) - [i17]Karthik Abinav Sankararaman, Anand Louis, Navin Goyal:
Robust Identifiability in Linear Structural Equation Models of Causal Inference. CoRR abs/2007.06869 (2020) - [i16]Sruthi Gorantla, Amit Deshpande, Anand Louis:
Ranking for Individual and Group Fairness Simultaneously. CoRR abs/2010.06986 (2020)
2010 – 2019
- 2019
- [c17]Amit Deshpande, Anand Louis, Apoorv Vikram Singh:
On Euclidean k-Means Clustering with alpha-Center Proximity. AISTATS 2019: 2087-2095 - [c16]Suprovat Ghoshal, Anand Louis, Rahul Raychaudhury:
Approximation Algorithms for Partially Colorable Graphs. APPROX-RANDOM 2019: 28:1-28:20 - [c15]Anand Louis, Rakesh Venkat:
Planted Models for k-Way Edge and Vertex Expansion. FSTTCS 2019: 23:1-23:15 - [c14]Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Vikram Nitin, Anand Louis, Partha P. Talukdar:
HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs. NeurIPS 2019: 1509-1520 - [c13]Karthik Abinav Sankararaman, Anand Louis, Navin Goyal:
Stability of Linear Structural Equation Models of Causal Inference. UAI 2019: 323-333 - [i15]Karthik Abinav Sankararaman, Anand Louis, Navin Goyal:
Stability of Linear Structural Equation Models of Causal Inference. CoRR abs/1905.06836 (2019) - [i14]Suprovat Ghoshal, Anand Louis, Rahul Raychaudhury:
Approximation Algorithms for Partially Colorable Graphs. CoRR abs/1908.11631 (2019) - [i13]Anand Louis, Rakesh Venkat:
Planted Models for k-way Edge and Vertex Expansion. CoRR abs/1910.08889 (2019) - 2018
- [j3]T.-H. Hubert Chan, Anand Louis, Zhihao Gavin Tang, Chenzi Zhang:
Spectral Properties of Hypergraph Laplacian and Approximation Algorithms. J. ACM 65(3): 15:1-15:48 (2018) - [c12]Anand Louis, Rakesh Venkat:
Semi-random Graphs with Planted Sparse Vertex Cuts: Algorithms for Exact and Approximate Recovery. ICALP 2018: 101:1-101:15 - [i12]Amit Deshpande, Anand Louis, Apoorv Vikram Singh:
Clustering Perturbation Resilient Instances. CoRR abs/1804.10827 (2018) - [i11]Anand Louis, Rakesh Venkat:
Semi-Random Graphs with Planted Sparse Vertex Cuts: Algorithms for Exact and Approximate Recovery. CoRR abs/1805.09747 (2018) - [i10]Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Anand Louis, Partha Pratim Talukdar:
HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification. CoRR abs/1809.02589 (2018) - 2017
- [c11]Akash Kumar, Anand Louis, Madhur Tulsiani:
Finding Pseudorandom Colorings of Pseudorandom Graphs. FSTTCS 2017: 37:1-37:12 - 2016
- [j2]Anand Louis, Yury Makarychev:
Approximation Algorithms for Hypergraph Small-Set Expansion and Small-Set Vertex Expansion. Theory Comput. 12(1): 1-25 (2016) - [c10]Anand Louis, Santosh S. Vempala:
Accelerated Newton Iteration for Roots of Black Box Polynomials. FOCS 2016: 732-740 - [i9]T.-H. Hubert Chan, Anand Louis, Zhihao Gavin Tang, Chenzi Zhang:
Spectral Properties of Hypergraph Laplacian and Approximation Algorithms. CoRR abs/1605.01483 (2016) - 2015
- [c9]Anand Louis:
Hypergraph Markov Operators, Eigenvalues and Approximation Algorithms. STOC 2015: 713-722 - [i8]Anand Louis, Santosh S. Vempala:
Accelerated Newton Iteration: Roots of Black Box Polynomials and Matrix Eigenvalues. CoRR abs/1511.03186 (2015) - 2014
- [c8]Anand Louis, Yury Makarychev:
Approximation Algorithms for Hypergraph Small Set Expansion and Small Set Vertex Expansion. APPROX-RANDOM 2014: 339-355 - [c7]Zachary Friggstad, Jochen Könemann, Young Kun-Ko, Anand Louis, Mohammad Shadravan, Madhur Tulsiani:
Linear Programming Hierarchies Suffice for Directed Steiner Tree. IPCO 2014: 285-296 - [c6]Anand Louis, Konstantin Makarychev:
Approximation Algorithm for Sparsest k-Partitioning. SODA 2014: 1244-1255 - [i7]Anand Louis, Yury Makarychev:
Approximation Algorithms for Hypergraph Small Set Expansion and Small Set Vertex Expansion. CoRR abs/1404.4575 (2014) - [i6]Anand Louis:
Hypergraph Markov Operators, Eigenvalues and Approximation Algorithms. CoRR abs/1408.2425 (2014) - 2013
- [j1]Ankit Aggarwal, Anand Louis, Manisha Bansal, Naveen Garg, Neelima Gupta, Shubham Gupta, Surabhi Jain:
A 3-approximation algorithm for the facility location problem with uniform capacities. Math. Program. 141(1-2): 527-547 (2013) - [c5]Anand Louis, Prasad Raghavendra, Santosh S. Vempala:
The Complexity of Approximating Vertex Expansion. FOCS 2013: 360-369 - [i5]Anand Louis, Prasad Raghavendra, Santosh S. Vempala:
The Complexity of Approximating Vertex Expansion. CoRR abs/1304.3139 (2013) - [i4]Anand Louis, Konstantin Makarychev:
Approximation Algorithm for Sparsest k-Partitioning. CoRR abs/1306.4384 (2013) - 2012
- [c4]Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala:
Many sparse cuts via higher eigenvalues. STOC 2012: 1131-1140 - 2011
- [c3]Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala:
Algorithmic Extensions of Cheeger's Inequality to Higher Eigenvalues and Partitions. APPROX-RANDOM 2011: 315-326 - [i3]Anand Louis, Prasad Raghavendra, Prasad Tetali, Santosh S. Vempala:
Many Sparse Cuts via Higher Eigenvalues. CoRR abs/1111.0965 (2011) - 2010
- [c2]Ankit Aggarwal, Anand Louis, Manisha Bansal, Naveen Garg, Neelima Gupta, Shubham Gupta, Surabhi Jain:
A 3-Approximation for Facility Location with Uniform Capacities. IPCO 2010: 149-162 - [c1]Anand Louis, Nisheeth K. Vishnoi:
Improved Algorithm for Degree Bounded Survivable Network Design Problem. SWAT 2010: 408-419 - [i2]Anand Louis:
Cut-Matching Games on Directed Graphs. CoRR abs/1010.1047 (2010)
2000 – 2009
- 2009
- [i1]Anand Louis, Nisheeth K. Vishnoi:
Improved Algorithm for Degree Bounded Survivable Network Design Problem. CoRR abs/0911.4544 (2009)
Coauthor Index
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