A 3-Approximation for Facility Location with Uniform Capacities. - Ankit Aggarwal; Anand Louis; Manisha Bansal; Naveen Garg 001; Neelima Gupta; Shubham Gupta; Surabhi Jain (IPCO, 2010)

Improved Algorithm for Degree Bounded Survivable Network Design Problem. - Anand Louis; Nisheeth K. Vishnoi (SWAT, 2010)

Cut-Matching Games on Directed Graphs - Anand Louis (CoRR, 2010)

Algorithmic Extensions of Cheeger's Inequality to Higher Eigenvalues and Partitions. - Anand Louis; Prasad Raghavendra; Prasad Tetali; Santosh S. Vempala (APPROX-RANDOM, 2011)

Many sparse cuts via higher eigenvalues. - Anand Louis; Prasad Raghavendra; Prasad Tetali; Santosh S. Vempala (STOC, 2012)

The Complexity of Approximating Vertex Expansion. - Anand Louis; Prasad Raghavendra; Santosh S. Vempala (FOCS, 2013)

Approximation Algorithm for Sparsest k-Partitioning. - Anand Louis; Konstantin Makarychev (CoRR, 2013)

A 3-approximation algorithm for the facility location problem with uniform capacities. - Ankit Aggarwal; Anand Louis; Manisha Bansal; Naveen Garg 001; Neelima Gupta; Shubham Gupta; Surabhi Jain (Math. Program., 2013)

Linear Programming Hierarchies Suffice for Directed Steiner Tree. - Zachary Friggstad; Jochen Könemann; Young Kun-Ko; Anand Louis; Mohammad Shadravan; Madhur Tulsiani (IPCO, 2014)

Approximation Algorithm for Sparsest k-Partitioning. - Anand Louis; Konstantin Makarychev (SODA, 2014)

The complexity of expansion problems. - Anand Louis (2014)

Hypergraph Markov Operators, Eigenvalues and Approximation Algorithms. - Anand Louis (STOC, 2015)

Accelerated Newton Iteration: Roots of Black Box Polynomials and Matrix Eigenvalues. - Anand Louis; Santosh S. Vempala (CoRR, 2015)

Accelerated Newton Iteration for Roots of Black Box Polynomials. - Anand Louis; Santosh S. Vempala (FOCS, 2016)

Approximation Algorithms for Hypergraph Small-Set Expansion and Small-Set Vertex Expansion. - Anand Louis; Yury Makarychev (Theory Comput., 2016)

Finding Pseudorandom Colorings of Pseudorandom Graphs. - Akash Kumar 003; Anand Louis; Madhur Tulsiani (FSTTCS, 2017)

Semi-random Graphs with Planted Sparse Vertex Cuts: Algorithms for Exact and Approximate Recovery. - Anand Louis; Rakesh Venkat (ICALP, 2018)

Clustering Perturbation Resilient Instances. - Amit Deshpande; Anand Louis; Apoorv Vikram Singh (CoRR, 2018)

HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification. - Naganand Yadati; Madhav Nimishakavi; Prateek Yadav; Anand Louis; Partha Pratim Talukdar (CoRR, 2018)

Spectral Properties of Hypergraph Laplacian and Approximation Algorithms. - T.-H. Hubert Chan; Anand Louis; Zhihao Gavin Tang; Chenzi Zhang (J. ACM, 2018)

On Euclidean k-Means Clustering with alpha-Center Proximity. - Amit Deshpande; Anand Louis; Apoorv Vikram Singh (AISTATS, 2019)

Approximation Algorithms for Partially Colorable Graphs. - Suprovat Ghoshal; Anand Louis; Rahul Raychaudhury (APPROX-RANDOM, 2019)

Planted Models for k-Way Edge and Vertex Expansion. - Anand Louis; Rakesh Venkat (FSTTCS, 2019)

HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs. - Naganand Yadati; Madhav Nimishakavi; Prateek Yadav; Vikram Nitin; Anand Louis; Partha P. Talukdar (NeurIPS, 2019)

Stability of Linear Structural Equation Models of Causal Inference. - Karthik Abinav Sankararaman; Anand Louis; Navin Goyal (UAI, 2019)

NHP: Neural Hypergraph Link Prediction. - Naganand Yadati; Vikram Nitin; Madhav Nimishakavi; Prateek Yadav; Anand Louis; Partha P. Talukdar (CIKM, 2020)

Planted Models for the Densest k-Subgraph Problem. - Yash Khanna; Anand Louis (FSTTCS, 2020)

On the Complexity and Approximation of λ∞ Spread Constant and Maximum Variance Embedding. - Majid Farhadi; Anand Louis; Prasad Tetali (CoRR, 2020)

Ranking for Individual and Group Fairness Simultaneously. - Sruthi Gorantla; Amit Deshpande; Anand Louis (CoRR, 2020)

Group Fairness for Knapsack Problems. - Deval Patel; Arindam Khan 001; Anand Louis (AAMAS, 2021)

On the Problem of Underranking in Group-Fair Ranking. - Sruthi Gorantla; Amit Deshpande; Anand Louis (ICML, 2021)

Matchings with Group Fairness Constraints: Online and Offline Algorithms. - Govind S. Sankar; Anand Louis; Meghana Nasre; Prajakta Nimbhorkar (IJCAI, 2021)

Graph Neural Networks for Soft Semi-Supervised Learning on Hypergraphs. - Naganand Yadati; Tingran Gao; Shahab Asoodeh; Partha P. Talukdar; Anand Louis (PAKDD (1), 2021)

Approximation Algorithms and Hardness for Strong Unique Games. - Suprovat Ghoshal; Anand Louis (SODA, 2021)

Independent Sets in Semi-random Hypergraphs. - Yash Khanna; Anand Louis; Rameesh Paul (WADS, 2021)

Approximating CSPs with Outliers. - Suprovat Ghoshal; Anand Louis (APPROX/RANDOM, 2022)

Exact Recovery Algorithm for Planted Bipartite Graph in Semi-Random Graphs. - Akash Kumar 003; Anand Louis; Rameesh Paul (ICALP, 2022)

Robust identifiability in linear structural equation models of causal inference. - Karthik Abinav Sankararaman; Anand Louis; Navin Goyal (UAI, 2022)

Sampling Random Group Fair Rankings. - Sruthi Gorantla; Amit Deshpande; Anand Louis (CoRR, 2022)

Bipartite Matchings with Group Fairness and Individual Fairness Constraints. - Atasi Panda; Anand Louis; Prajakta Nimbhorkar (CoRR, 2022)

Matchings Under Diversity Constraints. - Govind S. Sankar; Anand Louis; Meghana Nasre; Prajakta Nimbhorkar (CoRR, 2022)

Sampling Individually-Fair Rankings that are Always Group Fair. - Sruthi Gorantla; Anay Mehrotra; Amit Deshpande; Anand Louis (AIES, 2023)

Online Algorithms for Matchings with Proportional Fairness Constraints and Diversity Constraints. - Anand Louis; Meghana Nasre; Prajakta Nimbhorkar; Govind S. Sankar (ECAI, 2023)

Sampling Ex-Post Group-Fair Rankings. - Sruthi Gorantla; Amit Deshpande; Anand Louis (IJCAI, 2023)

Socially Fair Center-Based and Linear Subspace Clustering. - Sruthi Gorantla; Kishen N. Gowda; Amit Deshpande; Anand Louis (ECML/PKDD (1), 2023)

Optimizing Group-Fair Plackett-Luce Ranking Models for Relevance and Ex-Post Fairness. - Sruthi Gorantla; Eshaan Bhansali; Amit Deshpande; Anand Louis (CoRR, 2023)

Improved Linearly Ordered Colorings of Hypergraphs via SDP Rounding. - Anand Louis; Alantha Newman; Arka Ray (FSTTCS, 2024)

Individual Fairness under Group Fairness Constraints in Bipartite Matching - One Framework to Approximate Them All. - Atasi Panda; Anand Louis; Prajakta Nimbhorkar (IJCAI, 2024)

Optimizing Learning-to-Rank Models for Ex-Post Fair Relevance. - Sruthi Gorantla; Eshaan Bhansali; Amit Deshpande; Anand Louis (SIGIR, 2024)

New Approximation Bounds for Small-Set Vertex Expansion. - Suprovat Ghoshal; Anand Louis (SODA, 2024)

Sparse Cuts in Hypergraphs from Random Walks on Simplicial Complexes. - Anand Louis; Rameesh Paul; Arka Ray (SWAT, 2024)

On Sparsest Cut and Conductance in Directed Polymatroidal Networks. - Chandra Chekuri; Anand Louis (CoRR, 2024)

Robust Algorithms for Recovering Planted r-Colorable Graphs. - Anand Louis; Rameesh Paul; Prasad Raghavendra (COLT, 2025)