99 citations · 220 across the 16 of their papers we have counts for
19 papers
CEV-LM: Controlled Edit Vector Language Model for Shaping Natural Language Generations
Samraj Moorjani, Adit Krishnan, Hari Sundaram
As large-scale language models become the standard for text generation, there is a greater need to tailor the generations to be more or less concise, targeted, and informative, dep…
Pre-trained Neural Recommenders: A Transferable Zero-Shot Framework for Recommendation Systems
Junting Wang, Adit Krishnan, Hari Sundaram +1
Modern neural collaborative filtering techniques are critical to the success of e-commerce, social media, and content-sharing platforms. However, despite technical advances -- for…
Lower Bounds for Pseudo-Deterministic Counting in a Stream
Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan +1
Many streaming algorithms provide only a high-probability relative approximation. These two relaxations, of allowing approximation and randomization, seem necessary -- for many str…
Audience-Centric Natural Language Generation via Style Infusion
Samraj Moorjani, Adit Krishnan, Hari Sundaram +2
Adopting contextually appropriate, audience-tailored linguistic styles is critical to the success of user-centric language generation systems (e.g., chatbots, computer-aided writin…
ESW Edge-Weights : Ensemble Stochastic Watershed Edge-Weights for Hyperspectral Image Classification
Rohan Agarwal, Aman Aziz, Aditya Suraj Krishnan +2
Hyperspectral image (HSI) classification is a topic of active research. One of the main challenges of HSI classification is the lack of reliable labelled samples. Various semi-supe…
Projective Clustering Product Quantization
Aditya Krishnan, Edo Liberty
This paper suggests the use of projective clustering based product quantization for improving nearest neighbor and max-inner-product vector search (MIPS) algorithms. We provide ani…
Lifelong Learning with Sketched Structural Regularization
Haoran Li, Aditya Krishnan, Jingfeng Wu +3
Preventing catastrophic forgetting while continually learning new tasks is an essential problem in lifelong learning. Structural regularization (SR) refers to a family of algorithm…
Sublinear Time Spectral Density Estimation
Vladimir Braverman, Aditya Krishnan, Christopher Musco
We present a new sublinear time algorithm for approximating the spectral density (eigenvalue distribution) of an normalized graph adjacency or Laplacian matrix. The alg…
Near-Optimal Entrywise Sampling of Numerically Sparse Matrices
Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan +1
Many real-world data sets are sparse or almost sparse. One method to measure this for a matrix is the \emph{numerical sparsity}, denoted $\mathsf{ns}(…
Beyond Localized Graph Neural Networks: An Attributed Motif Regularization Framework
Aravind Sankar, Junting Wang, Adit Krishnan +1
We present InfoMotif, a new semi-supervised, motif-regularized, learning framework over graphs. We overcome two key limitations of message passing in popular graph neural networks…
Competitively Pricing Parking in a Tree
Max Bender, Jacob Gilbert, Aditya Krishnan +1
Motivated by demand-responsive parking pricing systems we consider posted-price algorithms for the online metrical matching problem and the online metrical searching problem in a t…
Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation
Adit Krishnan, Mahashweta Das, Mangesh Bendre +2
The rapid proliferation of new users and items on the social web has aggravated the gray-sheep user/long-tail item challenge in recommender systems. Historically, cross-domain co-c…
Discovering Strategic Behaviors for Collaborative Content-Production in Social Networks
Yuxin Xiao, Adit Krishnan, Hari Sundaram
Some social networks provide explicit mechanisms to allocate social rewards such as reputation based on user activity, while the mechanism is more opaque in other networks. Nonethe…
Inf-VAE: A Variational Autoencoder Framework to Integrate Homophily and Influence in Diffusion Prediction
Aravind Sankar, Xinyang Zhang, Adit Krishnan +1
Recent years have witnessed tremendous interest in understanding and predicting information spread on social media platforms such as Twitter, Facebook, etc. Existing diffusion pred…
An Induced Multi-Relational Framework for Answer Selection in Community Question Answer Platforms
Kanika Narang, Chaoqi Yang, Adit Krishnan +3
This paper addresses the question of identifying the best candidate answer to a question on Community Question Answer (CQA) forums. The problem is important because Individuals oft…
Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension
Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan +1
Spectral functions of large matrices contains important structural information about the underlying data, and is thus becoming increasingly important. Many times, large matrices re…
On Sketching the to norms
Aditya Krishnan, Sidhanth Mohanty, David P. Woodruff
We initiate the study of data dimensionality reduction, or sketching, for the norms. Given an matrix , the norm, denoted $\|A\|_{q \to p} = \sup_{…
Unsupervised Extraction of Representative Concepts from Scientific Literature
Adit Krishnan, Aravind Sankar, Shi Zhi +1
This paper studies the automated categorization and extraction of scientific concepts from titles of scientific articles, in order to gain a deeper understanding of their key contr…
Improving Latent User Models in Online Social Media
Adit Krishnan, Ashish Sharma, Hari Sundaram
Modern social platforms are characterized by the presence of rich user-behavior data associated with the publication, sharing and consumption of textual content. Users interact wit…